From Genome to Phenome
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PLATFORM ABSTRACTS Abstract Abstract Numbers Numbers Tuesday, November 6 41
American Society of Human Genetics 62nd Annual Meeting November 6–10, 2012 San Francisco, California PLATFORM ABSTRACTS Abstract Abstract Numbers Numbers Tuesday, November 6 41. Genes Underlying Neurological Disease Room 134 #196–#204 2. 4:30–6:30pm: Plenary Abstract 42. Cancer Genetics III: Common Presentations Hall D #1–#6 Variants Ballroom 104 #205–#213 43. Genetics of Craniofacial and Wednesday, November 7 Musculoskeletal Disorders Room 124 #214–#222 10:30am–12:45 pm: Concurrent Platform Session A (11–19): 44. Tools for Phenotype Analysis Room 132 #223–#231 11. Genetics of Autism Spectrum 45. Therapy of Genetic Disorders Room 130 #232–#240 Disorders Hall D #7–#15 46. Pharmacogenetics: From Discovery 12. New Methods for Big Data Ballroom 103 #16–#24 to Implementation Room 123 #241–#249 13. Cancer Genetics I: Rare Variants Room 135 #25–#33 14. Quantitation and Measurement of Friday, November 9 Regulatory Oversight by the Cell Room 134 #34–#42 8:00am–10:15am: Concurrent Platform Session D (47–55): 15. New Loci for Obesity, Diabetes, and 47. Structural and Regulatory Genomic Related Traits Ballroom 104 #43–#51 Variation Hall D #250–#258 16. Neuromuscular Disease and 48. Neuropsychiatric Disorders Ballroom 103 #259–#267 Deafness Room 124 #52–#60 49. Common Variants, Rare Variants, 17. Chromosomes and Disease Room 132 #61–#69 and Everything in-Between Room 135 #268–#276 18. Prenatal and Perinatal Genetics Room 130 #70–#78 50. Population Genetics Genome-Wide Room 134 #277–#285 19. Vascular and Congenital Heart 51. Endless Forms Most Beautiful: Disease Room 123 #79–#87 Variant Discovery in Genomic Data Ballroom 104 #286–#294 52. -
Supplementary Materials
Lists of figures Figure S1: A-B: Principal Component Analysis (PCA) was applied to 3 pairs of SCEC tissues (red) and matched adjacent normal tissues (blue) that were characterized by the gene expression of all probes on Affymetrix HG U133 Plus 2.0 Array. C: Box plot of SCEC group. D: Pearson’s correlation matrix of SCEC group. 17 / 25 Figure S2: MvA plot of SCEC group. Figure S3: Volcano plots of probe sets differing between SCEC and matched normal tissues. Fold change (X axis) is plotted against statistical significance (Y axis) for each probe sets. Genes altered with a fold change ≥2 and FDR <0.01 are depicted in red. Grey represents genes in the arrays that were not found to differ significantly between cancerous samples and matched normal samples. Figure S4: Gene regulatory network plotted by the top 120 DEGs (ranked by FDR) of SCEC groups. 18 / 25 Figure S5: DNA copy number change profiles in 3 pairs of SCEC samples. The CNVs frequency of the whole genome was analyzed by aCGH. Gains were marked in red and losses in bule. Lists of tables Table S1. Primers used in qRT-PCR for microarray gene expression validation Gene Forward Primer (5’-3’) Reverse Primer (5’-3’) Product β-actin AAGGTGACAGCAGTCGGTT TGTGTGGACTTGGGAGAGG 195bp INSM1 GTATTCGCTGTGTTCATGGTC CGCTACATACATAGAGAGCAGAG 79bp ASCL1 AACTCCCATCACCTCTAACA TGAGACGAAAGACACCAACT 120bp NRCAM GATGGCGAAGAATGAAGTT ACAGTGAGGGATAAGGTGTG 141bp NUF2 ATGATGCCAGTGAACTCTGAA GACTTGTCCGTTTTGCTTTTG 160bp 19 / 25 SNAP25 CCTGGATATGGGCAATGAGAT ACACGGGTGGGCACACTTA 146bp PTP4A3 GCTTCCTCATCACCCACAA CCGTACTTCTTCAGGTCCTCA -
Interpreting Human Genetic Variation with in Vivo Zebrafish Assays Erica E
Interpreting Human Genetic Variation With In Vivo Zebrafish Assays Erica E. Davis, PhD, Stephan Frangakis, BS, and Nicholas Katsanis, PhD Center for Human Disease Modeling Duke University Medical Center Durham, North Carolina © 20132015 Katsanis Interpreting Human Genetic Variation With In Vivo Zebrafish Assays 11 Introduction bona fide pathogenic mutations alone in the average NOTES Rapid advances and cost erosion in exome and human exome, studies have reported a median of 50– genome analysis of patients with both rare and 150 nonsense mutations, several in homozygosity, common genetic disorders have accelerated gene while the abundance of unique single nucleotide discovery and illuminated fundamental biological variants (SNVs) can be in the low-to-mid 100s mechanisms. The thrill of discovery has been (1000 Genomes Project Consortium et al., 2010). accompanied, however, by the sobering appreciation Importantly, the number of rare and ultra-rare SNVs that human genomes are burdened with a large has continued to increase proportionately to the number of rare and ultra-rare variants, thereby posing number of available exomes and genomes (Tennessen a significant challenge in dissecting both the effect of et al., 2012), indicating that we are unlikely to reach such alleles on protein function and the biological saturation of such alleles soon. These observations relevance of these events to patient pathology. In have generated a significant interpretive problem an effort to develop model systems that are able to for disease gene discovery and for clinical genomics, generate surrogates of human pathologies, a powerful as population-based arguments alone have been suite of tools has been developed in zebrafish, unable to dissect the contribution of the majority of taking advantage of the relatively small (compared these alleles to clinical phenotypes. -
The Fission Yeast Non-Coding Transcriptome
The Fission Yeast Non-Coding Transcriptome Sophie Radha Atkinson A thesis submitted for the degree of Doctor of Philosophy University College London September 2014 1 Declaration I, Sophie Radha Atkinson, 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 Long non-coding RNAs (lncRNAs) are emerging as important regulators of gene expression, although it remains unclear to what extent they contribute overall to the information flow from genotype to phenotype. Using strand-specific RNA- sequencing, I identify thousands of novel unstable, or cryptic, lncRNAs in Schizosaccharomyces pombe. The nuclear exosome, the RNAi pathway and the cytoplasmic exonuclease Exo2 represent three key pathways regulating lncRNAs in S. pombe, defining the overlapping classes of CUTs, RUTs and XUTs, respectively. The nuclear exosome and the RNAi pathway act cooperatively to control nuclear lncRNA expression, while the cytoplasmic Exo2 pathway is more distinct. Impairing both the nuclear exosome and the cytoplasmic exonuclease Exo2 is lethal in S. pombe. Importantly, I show that CUTs, RUTs and XUTs are stabilised under physiologically relevant growth conditions, with three key groups emerging: late meiotic RUTs/XUTs, early meiotic CUTs and quiescent CUTs. Late meiotic RUTs/XUTs tend to be antisense to protein-coding genes, and anti-correlate in expression with their sense loci. In contrast, early meiotic and quiescent CUTs tend to be transcribed divergently from protein-coding genes and positively correlate in expression with their mRNA partners. The current study provides an in-depth survey of the lncRNA repertoire of S. -
Biocuration 2016 - Posters
Biocuration 2016 - Posters Source: http://www.sib.swiss/events/biocuration2016/posters 1 RAM: A standards-based database for extracting and analyzing disease-specified concepts from the multitude of biomedical resources Jinmeng Jia and Tieliu Shi Each year, millions of people around world suffer from the consequence of the misdiagnosis and ineffective treatment of various disease, especially those intractable diseases and rare diseases. Integration of various data related to human diseases help us not only for identifying drug targets, connecting genetic variations of phenotypes and understanding molecular pathways relevant to novel treatment, but also for coupling clinical care and biomedical researches. To this end, we built the Rare disease Annotation & Medicine (RAM) standards-based database which can provide reference to map and extract disease-specified information from multitude of biomedical resources such as free text articles in MEDLINE and Electronic Medical Records (EMRs). RAM integrates disease-specified concepts from ICD-9, ICD-10, SNOMED-CT and MeSH (http://www.nlm.nih.gov/mesh/MBrowser.html) extracted from the Unified Medical Language System (UMLS) based on the UMLS Concept Unique Identifiers for each Disease Term. We also integrated phenotypes from OMIM for each disease term, which link underlying mechanisms and clinical observation. Moreover, we used disease-manifestation (D-M) pairs from existing biomedical ontologies as prior knowledge to automatically recognize D-M-specific syntactic patterns from full text articles in MEDLINE. Considering that most of the record-based disease information in public databases are textual format, we extracted disease terms and their related biomedical descriptive phrases from Online Mendelian Inheritance in Man (OMIM), National Organization for Rare Disorders (NORD) and Orphanet using UMLS Thesaurus. -
IL-1 Transcriptional Responses to Lipopolysaccharides Are Regulated by a Complex of RNA Binding Proteins
IL-1 Transcriptional Responses to Lipopolysaccharides Are Regulated by a Complex of RNA Binding Proteins This information is current as Lihua Shi, Li Song, Kelly Maurer, Ying Dou, Vishesh R. of October 1, 2021. Patel, Chun Su, Michelle E. Leonard, Sumei Lu, Kenyaita M. Hodge, Annabel Torres, Alessandra Chesi, Struan F. A. Grant, Andrew D. Wells, Zhe Zhang, Michelle A. Petri and Kathleen E. Sullivan J Immunol published online 17 January 2020 http://www.jimmunol.org/content/early/2020/01/16/jimmun Downloaded from ol.1900650 Supplementary http://www.jimmunol.org/content/suppl/2020/01/16/jimmunol.190065 http://www.jimmunol.org/ Material 0.DCSupplemental Why The JI? Submit online. • Rapid Reviews! 30 days* from submission to initial decision • No Triage! Every submission reviewed by practicing scientists by guest on October 1, 2021 • Fast Publication! 4 weeks from acceptance to publication *average Subscription Information about subscribing to The Journal of Immunology is online at: http://jimmunol.org/subscription Permissions Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html Email Alerts Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts The Journal of Immunology is published twice each month by The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2020 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. Published January 17, 2020, doi:10.4049/jimmunol.1900650 The Journal of Immunology IL-1 Transcriptional Responses to Lipopolysaccharides Are Regulated by a Complex of RNA Binding Proteins Lihua Shi,* Li Song,* Kelly Maurer,* Ying Dou,*,1 Vishesh R. -
M1BP Cooperates with CP190 to Activate Transcription at TAD Borders and Promote Chromatin Insulator Activity
ARTICLE https://doi.org/10.1038/s41467-021-24407-y OPEN M1BP cooperates with CP190 to activate transcription at TAD borders and promote chromatin insulator activity Indira Bag 1,2, Shue Chen 1,2,4, Leah F. Rosin 1,2,4, Yang Chen 1,2, Chen-Yu Liu3, Guo-Yun Yu3 & ✉ Elissa P. Lei 1,2 1234567890():,; Genome organization is driven by forces affecting transcriptional state, but the relationship between transcription and genome architecture remains unclear. Here, we identified the Drosophila transcription factor Motif 1 Binding Protein (M1BP) in physical association with the gypsy chromatin insulator core complex, including the universal insulator protein CP190. M1BP is required for enhancer-blocking and barrier activities of the gypsy insulator as well as its proper nuclear localization. Genome-wide, M1BP specifically colocalizes with CP190 at Motif 1-containing promoters, which are enriched at topologically associating domain (TAD) borders. M1BP facilitates CP190 chromatin binding at many shared sites and vice versa. Both factors promote Motif 1-dependent gene expression and transcription near TAD borders genome-wide. Finally, loss of M1BP reduces chromatin accessibility and increases both inter- and intra-TAD local genome compaction. Our results reveal physical and functional inter- action between CP190 and M1BP to activate transcription at TAD borders and mediate chromatin insulator-dependent genome organization. 1 Nuclear Organization and Gene Expression Section, Bethesda, MD, USA. 2 Laboratory of Biochemistry and Genetics, Bethesda, MD, USA. 3 Laboratory of Cellular and Developmental Biology, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA. ✉ 4These authors contributed equally: Shue Chen, Leah F. -
Figure S1. 17-Mer Distribution in the Yangtze Finless Porpoise Genome
Figure S1. 17-mer distribution in the Yangtze finless porpoise genome. The x-axis is 17-mer depth (X); the y-axis is the number of sequencing reads at that depth. Figure S2. Sequence depth distribution of the assembly data. The x-axis shows the sequencing depth (X) and the y-axis shows the number of bases at a given depth. The results demonstrate that 99% of bases sequencing depth is more than 20. Figure S3. Comparison of gene structure characteristics of Yangtze finless porpoise and other cetaceans. The x-axis represents the length of corresponding genetic element of exon number and the y-axis represents gene density. Figure S4. Phylogeny relationships between the Yangtze finless porpoise and other mammals reconstructed by RAxML with the GTR+G+I model. Table S1. Summary of sequenced reads Raw Reads Qualified Reads1 Total Read Sequence Physical Total Read Sequence Physical Library SRA Data Length Coverage2 Coverage2 Data Length Coverage2 Coverage2 Insert Size (bp) Number (Gb) (bp) (×) (×) (Gb) (bp) (×) (×) 289 58.94 150.00 23.67 22.80 57.84 149.75 23.23 22.41 SRR6923836 462 71.33 150.00 28.65 44.12 70.12 149.74 28.16 43.44 SRR6923837 624 67.47 150.00 27.10 56.36 63.90 149.67 25.66 53.50 SRR6923834 791 57.58 150.00 23.12 60.97 55.39 149.67 22.24 58.78 SRR6923835 4,000 108.73 150.00 43.67 582.22 70.74 150.00 28.41 378.80 SRR6923832 7,000 115.4 150.00 46.35 1,081.39 84.76 150.00 34.04 794.27 SRR6923833 11,000 107.37 150.00 43.12 1,581.08 79.78 150.00 32.04 1,174.81 SRR6923830 18,000 127.46 150.00 51.19 3,071.33 97.75 150.00 39.26 2,355.42 SRR6923831 Total 714.28 - 286.87 6,500.27 580.28 - 233.04 4,881.43 - 1Raw reads in mate-paired libraries were filtered to remove duplicates and reads with low quality and/or adapter contamination, raw reads in paired-end libraries were filtered in the same manner then subjected to k-mer-based correction. -
The 2014 Version of the Gene Table of Monogenic Neuromuscular Disorders (Nuclear Genome)
Available online at www.sciencedirect.com Neuromuscular Disorders 23 (2013) 1081–1111 www.elsevier.com/locate/nmd The 2014 version of the gene table of monogenic neuromuscular disorders (nuclear genome) Jean-Claude Kaplan a,⇑, Dalil Hamroun b a Institut Cochin, Universite´ Paris Descartes, 27 Rue du Faubourg Saint Jacques, 75014 Paris, France b Centre Hospitalo-Universitaire de Montpellier, Ho^pital Arnaud de Villeneuve, 34000 Montpellier, France General features as in LMNA defects) . In some diseases both kinds of heterogeneity may occur. As a consequence a gene or a This table is published annually in the December issue. Its disease may be cited in several places of the table. purpose is to provide the reader of Neuromuscular Disorders with an updated list of monogenic muscle diseases due to a The two versions of the gene table3 primary defect residing in the nuclear genome. It comprises diseases in which the causative gene is known or at least The annual printed version below is abridged and does localized on a chromosome, if not yet identified. Diseases not contain the Arrythmogenic Hereditary Cardiomyopa- for which the locus has not been mapped or which are due thies (Group 10-B), Hereditary Ataxias (Group 13), and to defects involving mitochondrial genes are not included.1 Hereditary Paraplegias (Group 15). The list of references is restricted to new key references corresponding to the As in past years the diseases are classified into 16 groups: items added or implemented since the preceding year. The full online version contains the complete data of the 1. Muscular dystrophies; 2. Congenital muscular dystro- 16 groups and the cumulative list of key references since 1991. -
How Abnormal RNA Metabolism Results in Childhood-Onset Neurological Diseases
Exosomal Protein Deficiencies: How Abnormal RNA Metabolism Results in Childhood-Onset Neurological Diseases A thesis submitted for the degree of Doctor of Philosophy at Newcastle University October 2016 Michele Giunta Institute of Genetic Medicine ii Author’s declaration This thesis is submitted for the degree of Doctor of Philosophy at Newcastle University. I, Michele Giunta, declare that the work described here is my own, unless where clearly acknowledged and stated otherwise. I certify that I have not submitted any of the material in this thesis for a degree qualification at this or any other university. iii Abstract RNA metabolism is of critical importance for normal cellular functions and needs to be finely tuned in order to maintain stable conditions within the cell. The exosome complex is the most important RNA processing machinery, responsible for the correct processing of many different types of RNAs and interacting with different co-factors which bind and carry specific subtypes of RNA for degradation to the complex. Mutations in exosome complex subunits (EXOSC3, EXOSC8) were reported to cause severe childhood onset complex neurological disorders presenting with pontocerebellar hypoplasia type 1 (PCH1), spinal muscular atrophy (SMA) and central nervous system hypomyelination. We have recently identified a homozygous pathogenic mutation in RNA Binding Motif Protein 7 RBM7, a subunit of the nuclear exosome targeting (NEXT) complex in a single patient with SMA-like phenotype and proved that RBM7 is a novel human disease gene related to the exosome complex. In order to understand the disease mechanism in RBM7 deficiency and to explore the role of exosome complex in neurodevelopment, we performed gene expression studies (RT-PCR, RNA sequencing) in human cells of patients carrying mutations in EXOSC8 and RBM7. -
Immune Gene Variation and Susceptibility to Upper Respiratory
Louisiana State University LSU Digital Commons LSU Doctoral Dissertations Graduate School 2016 Immune Gene Variation and Susceptibility to Upper Respiratory Tract Disease in Gopher Tortoises Jean Pierre Elbers Louisiana State University and Agricultural and Mechanical College, [email protected] Follow this and additional works at: https://digitalcommons.lsu.edu/gradschool_dissertations Part of the Environmental Sciences Commons Recommended Citation Elbers, Jean Pierre, "Immune Gene Variation and Susceptibility to Upper Respiratory Tract Disease in Gopher Tortoises" (2016). LSU Doctoral Dissertations. 4245. https://digitalcommons.lsu.edu/gradschool_dissertations/4245 This Dissertation is brought to you for free and open access by the Graduate School at LSU Digital Commons. It has been accepted for inclusion in LSU Doctoral Dissertations by an authorized graduate school editor of LSU Digital Commons. For more information, please [email protected]. IMMUNE GENE VARIATION AND SUSCEPTIBILTY TO UPPER RESPIRATORY TRACT DISEASE IN GOPHER TORTOISES A Dissertation Submitted to the Graduate Faculty of the Louisiana State University and Agricultural and Mechanical College in partial fulfillment of the requirements for the degree of Doctor of Philosophy in The School of Renewable Natural Resources by Jean Pierre Elbers B.S., Southeastern Louisiana University, 2008 M.S., Missouri State University, 2010 December 2016 ACKNOWLEDGEMENTS Let me begin by first thanking my wonderful advisor, Sabrina Taylor. She has shown interest and care in not only my dissertation project but also my development as person, researcher, and scientist. I have been truly thankful to work under her tutelage and guidance: thank you so much Sabrina! Next I would like to thank the Lucius Wilmot Gilbert Foundation for Forestry Research, which provided funding for not only my research projects but also for my research assistantship at Louisiana State University. -
NIH Public Access Author Manuscript Nat Rev Mol Cell Biol
NIH Public Access Author Manuscript Nat Rev Mol Cell Biol. Author manuscript; available in PMC 2015 February 01. NIH-PA Author ManuscriptPublished NIH-PA Author Manuscript in final edited NIH-PA Author Manuscript form as: Nat Rev Mol Cell Biol. 2014 February ; 15(2): 108–121. doi:10.1038/nrm3742. A day in the life of the spliceosome A. Gregory Matera1,2,4,5 and Zefeng Wang3,4 1Department of Biology, University of North Carolina, Chapel Hill, NC 27599 2Department of Genetics, University of North Carolina, Chapel Hill, NC 27599 3Department of Pharmacology, University of North Carolina, Chapel Hill, NC 27599 4Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC 27599 5Integrative Program for Biological and Genome Sciences, University of North Carolina, Chapel Hill, NC 27599 Abstract One of the most amazing findings in molecular biology was the discovery that eukaryotic genes are discontinuous, interrupted by stretches of non-coding sequence. The subsequent realization that the intervening regions are removed from pre-mRNA transcripts via the activity of a common set of small nuclear RNAs (snRNAs), which assemble together with associated proteins into a spliceosome, was equally surprising. How do cells orchestrate the assembly of this molecular machine? And how does the spliceosome accurately recognize exons and introns to carry out the splicing reaction? Insights into these questions have been gained by studying the life cycle of spliceosomal snRNAs from their transcription, nuclear export and reimport, all the way through to their dynamic assembly into the spliceosome. This assembly process can also affect the regulation of alternative splicing and has implications for human disease.