The Genetic Basis of Emotional Behaviour in Mice
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Table 2. Functional Classification of Genes Differentially Regulated After HOXB4 Inactivation in HSC/Hpcs
Table 2. Functional classification of genes differentially regulated after HOXB4 inactivation in HSC/HPCs Symbol Gene description Fold-change (mean ± SD) Signal transduction Adam8 A disintegrin and metalloprotease domain 8 1.91 ± 0.51 Arl4 ADP-ribosylation factor-like 4 - 1.80 ± 0.40 Dusp6 Dual specificity phosphatase 6 (Mkp3) - 2.30 ± 0.46 Ksr1 Kinase suppressor of ras 1 1.92 ± 0.42 Lyst Lysosomal trafficking regulator 1.89 ± 0.34 Mapk1ip1 Mitogen activated protein kinase 1 interacting protein 1 1.84 ± 0.22 Narf* Nuclear prelamin A recognition factor 2.12 ± 0.04 Plekha2 Pleckstrin homology domain-containing. family A. (phosphoinosite 2.15 ± 0.22 binding specific) member 2 Ptp4a2 Protein tyrosine phosphatase 4a2 - 2.04 ± 0.94 Rasa2* RAS p21 activator protein 2 - 2.80 ± 0.13 Rassf4 RAS association (RalGDS/AF-6) domain family 4 3.44 ± 2.56 Rgs18 Regulator of G-protein signaling - 1.93 ± 0.57 Rrad Ras-related associated with diabetes 1.81 ± 0.73 Sh3kbp1 SH3 domain kinase bindings protein 1 - 2.19 ± 0.53 Senp2 SUMO/sentrin specific protease 2 - 1.97 ± 0.49 Socs2 Suppressor of cytokine signaling 2 - 2.82 ± 0.85 Socs5 Suppressor of cytokine signaling 5 2.13 ± 0.08 Socs6 Suppressor of cytokine signaling 6 - 2.18 ± 0.38 Spry1 Sprouty 1 - 2.69 ± 0.19 Sos1 Son of sevenless homolog 1 (Drosophila) 2.16 ± 0.71 Ywhag 3-monooxygenase/tryptophan 5- monooxygenase activation protein. - 2.37 ± 1.42 gamma polypeptide Zfyve21 Zinc finger. FYVE domain containing 21 1.93 ± 0.57 Ligands and receptors Bambi BMP and activin membrane-bound inhibitor - 2.94 ± 0.62 -
Global H3k4me3 Genome Mapping Reveals Alterations of Innate Immunity Signaling and Overexpression of JMJD3 in Human Myelodysplastic Syndrome CD34 Þ Cells
Leukemia (2013) 27, 2177–2186 & 2013 Macmillan Publishers Limited All rights reserved 0887-6924/13 www.nature.com/leu ORIGINAL ARTICLE Global H3K4me3 genome mapping reveals alterations of innate immunity signaling and overexpression of JMJD3 in human myelodysplastic syndrome CD34 þ cells YWei1, R Chen2, S Dimicoli1, C Bueso-Ramos3, D Neuberg4, S Pierce1, H Wang2, H Yang1, Y Jia1, H Zheng1, Z Fang1, M Nguyen3, I Ganan-Gomez1,5, B Ebert6, R Levine7, H Kantarjian1 and G Garcia-Manero1 The molecular bases of myelodysplastic syndromes (MDS) are not fully understood. Trimethylated histone 3 lysine 4 (H3K4me3) is present in promoters of actively transcribed genes and has been shown to be involved in hematopoietic differentiation. We performed a genome-wide H3K4me3 CHIP-Seq (chromatin immunoprecipitation coupled with whole genome sequencing) analysis of primary MDS bone marrow (BM) CD34 þ cells. This resulted in the identification of 36 genes marked by distinct higher levels of promoter H3K4me3 in MDS. A majority of these genes are involved in nuclear factor (NF)-kB activation and innate immunity signaling. We then analyzed expression of histone demethylases and observed significant overexpression of the JmjC-domain histone demethylase JMJD3 (KDM6b) in MDS CD34 þ cells. Furthermore, we demonstrate that JMJD3 has a positive effect on transcription of multiple CHIP-Seq identified genes involved in NF-kB activation. Inhibition of JMJD3 using shRNA in primary BM MDS CD34 þ cells resulted in an increased number of erythroid colonies in samples isolated from patients with lower-risk MDS. Taken together, these data indicate the deregulation of H3K4me3 and associated abnormal activation of innate immunity signals have a role in the pathogenesis of MDS and that targeting these signals may have potential therapeutic value in MDS. -
Identification of Key Pathways and Genes in Dementia Via Integrated Bioinformatics Analysis
bioRxiv preprint doi: https://doi.org/10.1101/2021.04.18.440371; this version posted July 19, 2021. 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. Identification of Key Pathways and Genes in Dementia via Integrated Bioinformatics Analysis Basavaraj Vastrad1, Chanabasayya Vastrad*2 1. Department of Biochemistry, Basaveshwar College of Pharmacy, Gadag, Karnataka 582103, India. 2. Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karnataka, India. * Chanabasayya Vastrad [email protected] Ph: +919480073398 Chanabasava Nilaya, Bharthinagar, Dharwad 580001 , Karanataka, India bioRxiv preprint doi: https://doi.org/10.1101/2021.04.18.440371; this version posted July 19, 2021. 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. Abstract To provide a better understanding of dementia at the molecular level, this study aimed to identify the genes and key pathways associated with dementia by using integrated bioinformatics analysis. Based on the expression profiling by high throughput sequencing dataset GSE153960 derived from the Gene Expression Omnibus (GEO), the differentially expressed genes (DEGs) between patients with dementia and healthy controls were identified. With DEGs, we performed a series of functional enrichment analyses. Then, a protein–protein interaction (PPI) network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network was constructed, analyzed and visualized, with which the hub genes miRNAs and TFs nodes were screened out. Finally, validation of hub genes was performed by using receiver operating characteristic curve (ROC) analysis. -
Genome Sequencing Unveils a Regulatory Landscape of Platelet Reactivity
ARTICLE https://doi.org/10.1038/s41467-021-23470-9 OPEN Genome sequencing unveils a regulatory landscape of platelet reactivity Ali R. Keramati 1,2,124, Ming-Huei Chen3,4,124, Benjamin A. T. Rodriguez3,4,5,124, Lisa R. Yanek 2,6, Arunoday Bhan7, Brady J. Gaynor 8,9, Kathleen Ryan8,9, Jennifer A. Brody 10, Xue Zhong11, Qiang Wei12, NHLBI Trans-Omics for Precision (TOPMed) Consortium*, Kai Kammers13, Kanika Kanchan14, Kruthika Iyer14, Madeline H. Kowalski15, Achilleas N. Pitsillides4,16, L. Adrienne Cupples 4,16, Bingshan Li 12, Thorsten M. Schlaeger7, Alan R. Shuldiner9, Jeffrey R. O’Connell8,9, Ingo Ruczinski17, Braxton D. Mitchell 8,9, ✉ Nauder Faraday2,18, Margaret A. Taub17, Lewis C. Becker1,2, Joshua P. Lewis 8,9,125 , 2,14,125✉ 3,4,125✉ 1234567890():,; Rasika A. Mathias & Andrew D. Johnson Platelet aggregation at the site of atherosclerotic vascular injury is the underlying patho- physiology of myocardial infarction and stroke. To build upon prior GWAS, here we report on 16 loci identified through a whole genome sequencing (WGS) approach in 3,855 NHLBI Trans-Omics for Precision Medicine (TOPMed) participants deeply phenotyped for platelet aggregation. We identify the RGS18 locus, which encodes a myeloerythroid lineage-specific regulator of G-protein signaling that co-localizes with expression quantitative trait loci (eQTL) signatures for RGS18 expression in platelets. Gene-based approaches implicate the SVEP1 gene, a known contributor of coronary artery disease risk. Sentinel variants at RGS18 and PEAR1 are associated with thrombosis risk and increased gastrointestinal bleeding risk, respectively. Our WGS findings add to previously identified GWAS loci, provide insights regarding the mechanism(s) by which genetics may influence cardiovascular disease risk, and underscore the importance of rare variant and regulatory approaches to identifying loci contributing to complex phenotypes. -
Transcriptomic and Epigenomic Characterization of the Developing Bat Wing
ARTICLES OPEN Transcriptomic and epigenomic characterization of the developing bat wing Walter L Eckalbar1,2,9, Stephen A Schlebusch3,9, Mandy K Mason3, Zoe Gill3, Ash V Parker3, Betty M Booker1,2, Sierra Nishizaki1,2, Christiane Muswamba-Nday3, Elizabeth Terhune4,5, Kimberly A Nevonen4, Nadja Makki1,2, Tara Friedrich2,6, Julia E VanderMeer1,2, Katherine S Pollard2,6,7, Lucia Carbone4,8, Jeff D Wall2,7, Nicola Illing3 & Nadav Ahituv1,2 Bats are the only mammals capable of powered flight, but little is known about the genetic determinants that shape their wings. Here we generated a genome for Miniopterus natalensis and performed RNA-seq and ChIP-seq (H3K27ac and H3K27me3) analyses on its developing forelimb and hindlimb autopods at sequential embryonic stages to decipher the molecular events that underlie bat wing development. Over 7,000 genes and several long noncoding RNAs, including Tbx5-as1 and Hottip, were differentially expressed between forelimb and hindlimb, and across different stages. ChIP-seq analysis identified thousands of regions that are differentially modified in forelimb and hindlimb. Comparative genomics found 2,796 bat-accelerated regions within H3K27ac peaks, several of which cluster near limb-associated genes. Pathway analyses highlighted multiple ribosomal proteins and known limb patterning signaling pathways as differentially regulated and implicated increased forelimb mesenchymal condensation in differential growth. In combination, our work outlines multiple genetic components that likely contribute to bat wing formation, providing insights into this morphological innovation. The order Chiroptera, commonly known as bats, is the only group of To characterize the genetic differences that underlie divergence in mammals to have evolved the capability of flight. -
Supplementary Information.Pdf
Supplementary Information Whole transcriptome profiling reveals major cell types in the cellular immune response against acute and chronic active Epstein‐Barr virus infection Huaqing Zhong1, Xinran Hu2, Andrew B. Janowski2, Gregory A. Storch2, Liyun Su1, Lingfeng Cao1, Jinsheng Yu3, and Jin Xu1 Department of Clinical Laboratory1, Children's Hospital of Fudan University, Minhang District, Shanghai 201102, China; Departments of Pediatrics2 and Genetics3, Washington University School of Medicine, Saint Louis, Missouri 63110, United States. Supplementary information includes the following: 1. Supplementary Figure S1: Fold‐change and correlation data for hyperactive and hypoactive genes. 2. Supplementary Table S1: Clinical data and EBV lab results for 110 study subjects. 3. Supplementary Table S2: Differentially expressed genes between AIM vs. Healthy controls. 4. Supplementary Table S3: Differentially expressed genes between CAEBV vs. Healthy controls. 5. Supplementary Table S4: Fold‐change data for 303 immune mediators. 6. Supplementary Table S5: Primers used in qPCR assays. Supplementary Figure S1. Fold‐change (a) and Pearson correlation data (b) for 10 cell markers and 61 hypoactive and hyperactive genes identified in subjects with acute EBV infection (AIM) in the primary cohort. Note: 23 up‐regulated hyperactive genes were highly correlated positively with cytotoxic T cell (Tc) marker CD8A and NK cell marker CD94 (KLRD1), and 38 down‐regulated hypoactive genes were highly correlated positively with B cell, conventional dendritic cell -
Different Contribution of BRINP3 Gene in Chronic
Casado et al. BMC Oral Health (2015) 15:33 DOI 10.1186/s12903-015-0018-6 RESEARCH ARTICLE Open Access Different contribution of BRINP3 gene in chronic periodontitis and peri-implantitis: a cross- sectional study Priscila L Casado1,2, Diego P Aguiar2, Lucas C Costa3, Marcos A Fonseca3, Thays CS Vieira2,4, Claudia CK Alvim-Pereira5, Fabiano Alvim-Pereira6, Kathleen Deeley7, José M Granjeiro1,9, Paula C Trevilatto8 and Alexandre R Vieira7,10* Abstract Background: Peri-implantitis is a chronic inflammation, resulting in loss of supporting bone around implants. Chronic periodontitis is a risk indicator for implant failure. Both diseases have a common etiology regarding inflammatory destructive response. BRINP3 gene is associated with aggressive periodontitis. However, is still unclear if chronic periodontitis and peri-implantitis have the same genetic background. The aim of this work was to investigate the association between BRINP3 genetic variation (rs1342913 and rs1935881) and expression and susceptibility to both diseases. Methods: Periodontal and peri-implant examinations were performed in 215 subjects, divided into: healthy (without chronic periodontitis and peri-implantitis, n = 93); diseased (with chronic periodontitis and peri-implantitis, n = 52); chronic periodontitis only (n = 36), and peri-implantitis only (n = 34). A replication sample of 92 subjects who lost implants and 185 subjects successfully treated with implants were tested. DNA was extracted from buccal cells. Two genetic markers of BRINP3 (rs1342913 and rs1935881) were genotyped using TaqMan chemistry. Chi-square (p < 0.05) compared genotype and allele frequency between groups. A subset of subjects (n = 31) had gingival biopsies ΔΔCT harvested. The BRINP3 mRNA levels were studied by CT method (2 ). -
Biological Role and Disease Impact of Copy Number Variation in Complex Disease
University of Pennsylvania ScholarlyCommons Publicly Accessible Penn Dissertations 2014 Biological Role and Disease Impact of Copy Number Variation in Complex Disease Joseph Glessner University of Pennsylvania, [email protected] Follow this and additional works at: https://repository.upenn.edu/edissertations Part of the Bioinformatics Commons, and the Genetics Commons Recommended Citation Glessner, Joseph, "Biological Role and Disease Impact of Copy Number Variation in Complex Disease" (2014). Publicly Accessible Penn Dissertations. 1286. https://repository.upenn.edu/edissertations/1286 This paper is posted at ScholarlyCommons. https://repository.upenn.edu/edissertations/1286 For more information, please contact [email protected]. Biological Role and Disease Impact of Copy Number Variation in Complex Disease Abstract In the human genome, DNA variants give rise to a variety of complex phenotypes. Ranging from single base mutations to copy number variations (CNVs), many of these variants are neutral in selection and disease etiology, making difficult the detection of true common orar r e frequency disease-causing mutations. However, allele frequency comparisons in cases, controls, and families may reveal disease associations. Single nucleotide polymorphism (SNP) arrays and exome sequencing are popular assays for genome-wide variant identification. oT limit bias between samples, uniform testing is crucial, including standardized platform versions and sample processing. Bases occupy single points while copy variants occupy segments. -
Castration Delays Epigenetic Aging and Feminizes DNA
RESEARCH ARTICLE Castration delays epigenetic aging and feminizes DNA methylation at androgen- regulated loci Victoria J Sugrue1, Joseph Alan Zoller2, Pritika Narayan3, Ake T Lu4, Oscar J Ortega-Recalde1, Matthew J Grant3, C Simon Bawden5, Skye R Rudiger5, Amin Haghani4, Donna M Bond1, Reuben R Hore6, Michael Garratt1, Karen E Sears7, Nan Wang8, Xiangdong William Yang8,9, Russell G Snell3, Timothy A Hore1†*, Steve Horvath4†* 1Department of Anatomy, University of Otago, Dunedin, New Zealand; 2Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, United States; 3Applied Translational Genetics Group, School of Biological Sciences, Centre for Brain Research, The University of Auckland, Auckland, New Zealand; 4Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, United States; 5Livestock and Farming Systems, South Australian Research and Development Institute, Roseworthy, Australia; 6Blackstone Hill Station, Becks, RD2, Omakau, New Zealand; 7Department of Ecology and Evolutionary Biology, UCLA, Los Angeles, United States; 8Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles (UCLA), Los Angeles, United States; 9Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, United States *For correspondence: Abstract In mammals, females generally live longer than males. Nevertheless, the mechanisms [email protected] (TAH); underpinning sex-dependent longevity are currently unclear. Epigenetic clocks are powerful [email protected] (SH) biological biomarkers capable of precisely estimating chronological age and identifying novel †These authors contributed factors influencing the aging rate using only DNA methylation data. In this study, we developed the equally to this work first epigenetic clock for domesticated sheep (Ovis aries), which can predict chronological age with a median absolute error of 5.1 months. -
RGS18 (F-5): Sc-390908
SANTA CRUZ BIOTECHNOLOGY, INC. RGS18 (F-5): sc-390908 BACKGROUND APPLICATIONS The regulators of G protein signaling (RGS) proteins inhibit heterotrimeric G RGS18 (F-5) is recommended for detection of RGS18 of human origin by protein signaling. RGS proteins work by functioning as GTPase-activating Western Blotting (starting dilution 1:100, dilution range 1:100-1:1000), proteins (which increase the GTPase activity of G protein a subunits) thereby immunoprecipitation [1-2 µg per 100-500 µg of total protein (1 ml of cell driving G proteins into their inactive GDP-bound form. RGS18 is a 234 amino lysate)], immunofluorescence (starting dilution 1:50, dilution range 1:50- acid peptide expressed mainly in megakaryocyte cells, but also in hemato- 1:500) and solid phase ELISA (starting dilution 1:30, dilution range 1:30- poietic progenitor and myeloerythroid lineage cells. RGS18 expression is 1:3000). upregulated during megakaryocyte differentiation and may play an important Suitable for use as control antibody for RGS18 siRNA (h): sc-61468, RGS18 role in the mediation of megakaryocyte chemotaxis. Structurally, RGS18 con- shRNA Plasmid (h): sc-61468-SH and RGS18 shRNA (h) Lentiviral Particles: tains phosphorylation sites for casein kinase II, protein kinase C and protein sc-61468-V. kinase A. RGS18 specifically binds to two a subunits of the G protein, Ga i and Ga q. Molecular Weight of RGS18: 26 kDa. Positive Controls: human RGS18 transfected HEK293T whole cell lysate. REFERENCES 1. Yowe, D., et al. 2001. RGS18 is a myeloerythroid lineage-specific regula- RECOMMENDED SUPPORT REAGENTS tor of molecule highly expressed in megakaryocytes. -
Integrated Genetic Diagnosis of Neurofibromatosis Type 1 (NF1) and Molecular Characterization of One Case of Compound Heterozygosity
Integrated genetic diagnosis of Neurofibromatosis type 1 (NF1) and molecular characterization of one case of compound heterozygosity Coordinator: Prof. Andrea Biondi Tutor: Dr. Gaetano Finocchiaro Dr. Sara MOROSINI Matr. No. 745001 XXVI CYCLE ACADEMIC YEAR 2012-2013 2 A Fabio e Matteo 3 4 TABLE of CONTENTS CHAPTER 1 7 INTRODUCTION 7 Neurofibromatoses 7 Neurofibromatosis type 1 8 Genotype/Phenotype correlation 24 NF1 gene 26 NF1 Protein 30 SCOPE OF THE THESIS 34 REFERENCES 36 CHAPTER 2 49 A TEN YEAR OF ITALIAN EXPERIENCE IN NEUROFIBROMATOSIS TYPE 1: 102 NOVEL MUTATIONS 49 CHAPTER 3 94 INTEGRATED GENETIC STUDIES OF NEUROFIBROMATOSIS TYPE 1. 94 CHAPTER 4 113 A FAMILY CASE REPORT 113 CHAPTER 5 138 SUMMARY 138 5 CONCLUSION 140 FUTURE PERSPECTIVES 142 ACKNOWLEDGEMENTS 146 6 Chapter 1 INTRODUCTION Neurofibromatoses Historically the neurofibromatosis type 1 (NF1), type 2 (NF2) and schwannomatosis were referred with the common terms of Neurofibromatosis. Neurofibromatoses are a group of conditions that predispose to tumors of the nervous system and abnormal skin pigmentation. Each type is defined by the presence/absence of café au lait (CAL) spots and skinfold freckling, what kind of peripheral nerve tumor develops (neurofibromas vs. schwannomas) and other features, particularly in the eye, specific to each form. The neurofibromatoses, predisposing to multiple tumors of the peripheral nervous system, are often considered classical tumor suppressor diseases. Longitudinal care for individuals with neurofibromatosis aims at the early detection and symptomatic treatment of complications as they occur 1. Very much has been elucidated about the complex molecular mechanism leading to these diseases. In the last two decades of the last century, the modern methods of genetic research showed that NF1 and NF2 had distinct clinical and genetic features. -
Expression Analysis and Functional Characterization of the Dro1/Cl2 Gene During Zebrafish Somitogenesis
See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/271208226 Expression analysis and functional characterization of the dro1/Cl2 gene during zebrafish somitogenesis Conference Paper · July 2009 DOI: 10.13140/2.1.2295.8407 CITATIONS READS 0 159 11 authors, including: Isabella Della Noce Elena Turola Parco Tecnologico Padano Università degli Studi di Modena e Reggio E… 16 PUBLICATIONS 19 CITATIONS 36 PUBLICATIONS 705 CITATIONS SEE PROFILE SEE PROFILE Silvia Carra Rosina Critelli I.R.C.C.S. Istituto Auxologico Italiano Università degli Studi di Modena e Reggio E… 38 PUBLICATIONS 132 CITATIONS 30 PUBLICATIONS 470 CITATIONS SEE PROFILE SEE PROFILE Some of the authors of this publication are also working on these related projects: Developmental Biology View project Mitogenome analysis of Sparidae species View project All content following this page was uploaded by Carlo De Lorenzo on 23 January 2015. The user has requested enhancement of the downloaded file. 6th European Zebrafish Genetics and Development Meeting Rome 15th - 19th July 2009 Program & Abstracts *UKVTUDMJDLFE DMJDLTBXBZGSPNQVSF%/" 8IZTBZEFPYZSJCPOVDMFJDBDJEXIFO%/"EPFTUIFKPC 8IZXPSLNJOVUFTPO%/"FYUSBDUJPOXIFOZPVDBOEPJUJO 8IZTQFOENPSFUIBOEPVCMFPOTPNFUIJOHMFTTUIBO(FOF.PMF (FOF.PMFJTBOJEFBMTZTUFNGPSBVUPNBUFE%/"BOE3/"FYUSBDUJPO 4JNQMFUPCVZ TJNQMFUPVTF BOETJNQMFUPNBJOUBJO (FOF.PMFJTWFSJ¾FEGPS[FCSB¾TITBNQMFTCZXPSMEMFBEJOHSFTFBSDIFST 6th European Zebrafish Genetics and Development Meeting Rome 15th - 19th July 2009 Program