X-Linked Intellectual Disability (Revised April 2021)
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Identification of Key Pathways and Genes in Endometrial Cancer Using Bioinformatics Analyses
ONCOLOGY LETTERS 17: 897-906, 2019 Identification of key pathways and genes in endometrial cancer using bioinformatics analyses YAN LIU, TENG HUA, SHUQI CHI and HONGBO WANG Department of Obstetrics and Gynecology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430022, P.R. China Received March 16, 2018; Accepted October 12, 2018 DOI: 10.3892/ol.2018.9667 Abstract. Endometrial cancer (EC) is one of the most Introduction common gynecological cancer types worldwide. However, to the best of our knowledge, its underlying mechanisms Endometrial carcinoma (EC) is one of the most common remain unknown. The current study downloaded three mRNA gynecological cancer types, with increasing global incidence and microRNA (miRNA) datasets of EC and normal tissue in recent years (1). A total of 60,050 cases of EC and 10,470 samples, GSE17025, GSE63678 and GSE35794, from the EC-associated cases of mortality were reported in the USA in Gene Expression Omnibus to identify differentially expressed 2016 (1), which was markedly higher than the 2012 statistics genes (DEGs) and miRNAs (DEMs) in EC tumor tissues. of 47,130 cases and 8,010 mortalities (2). Although numerous The DEGs and DEMs were then validated using data from studies have been conducted to investigate the mechanisms of The Cancer Genome Atlas and subjected to gene ontology endometrial tumorigenesis and development, to the best of our and Kyoto Encyclopedia of Genes and Genomes pathway knowledge, the exact etiology remains unknown. Understanding analysis. STRING and Cytoscape were used to construct a the potential molecular mechanisms underlying EC initiation protein-protein interaction network and the prognostic effects and progression is of great clinical significance. -
Coupling of Spliceosome Complexity to Intron Diversity
bioRxiv preprint doi: https://doi.org/10.1101/2021.03.19.436190; this version posted March 20, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.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. Coupling of spliceosome complexity to intron diversity Jade Sales-Lee1, Daniela S. Perry1, Bradley A. Bowser2, Jolene K. Diedrich3, Beiduo Rao1, Irene Beusch1, John R. Yates III3, Scott W. Roy4,6, and Hiten D. Madhani1,6,7 1Dept. of Biochemistry and Biophysics University of California – San Francisco San Francisco, CA 94158 2Dept. of Molecular and Cellular Biology University of California - Merced Merced, CA 95343 3Department of Molecular Medicine The Scripps Research Institute, La Jolla, CA 92037 4Dept. of Biology San Francisco State University San Francisco, CA 94132 5Chan-Zuckerberg Biohub San Francisco, CA 94158 6Corresponding authors: [email protected], [email protected] 7Lead Contact 1 bioRxiv preprint doi: https://doi.org/10.1101/2021.03.19.436190; this version posted March 20, 2021. 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. SUMMARY We determined that over 40 spliceosomal proteins are conserved between many fungal species and humans but were lost during the evolution of S. cerevisiae, an intron-poor yeast with unusually rigid splicing signals. We analyzed null mutations in a subset of these factors, most of which had not been investigated previously, in the intron-rich yeast Cryptococcus neoformans. -
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. -
Ageing-Associated Changes in DNA Methylation in X and Y Chromosomes
Kananen and Marttila Epigenetics & Chromatin (2021) 14:33 Epigenetics & Chromatin https://doi.org/10.1186/s13072-021-00407-6 RESEARCH Open Access Ageing-associated changes in DNA methylation in X and Y chromosomes Laura Kananen1,2,3,4* and Saara Marttila4,5* Abstract Background: Ageing displays clear sexual dimorphism, evident in both morbidity and mortality. Ageing is also asso- ciated with changes in DNA methylation, but very little focus has been on the sex chromosomes, potential biological contributors to the observed sexual dimorphism. Here, we sought to identify DNA methylation changes associated with ageing in the Y and X chromosomes, by utilizing datasets available in data repositories, comprising in total of 1240 males and 1191 females, aged 14–92 years. Results: In total, we identifed 46 age-associated CpG sites in the male Y, 1327 age-associated CpG sites in the male X, and 325 age-associated CpG sites in the female X. The X chromosomal age-associated CpGs showed signifcant overlap between females and males, with 122 CpGs identifed as age-associated in both sexes. Age-associated X chro- mosomal CpGs in both sexes were enriched in CpG islands and depleted from gene bodies and showed no strong trend towards hypermethylation nor hypomethylation. In contrast, the Y chromosomal age-associated CpGs were enriched in gene bodies, and showed a clear trend towards hypermethylation with age. Conclusions: Signifcant overlap in X chromosomal age-associated CpGs identifed in males and females and their shared features suggest that despite the uneven chromosomal dosage, diferences in ageing-associated DNA methylation changes in the X chromosome are unlikely to be a major contributor of sex dimorphism in ageing. -
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Patterns of DNA methylation on the human X chromosome and use in analyzing X-chromosome inactivation by Allison Marie Cotton B.Sc., The University of Guelph, 2005 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in The Faculty of Graduate Studies (Medical Genetics) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) January 2012 © Allison Marie Cotton, 2012 Abstract The process of X-chromosome inactivation achieves dosage compensation between mammalian males and females. In females one X chromosome is transcriptionally silenced through a variety of epigenetic modifications including DNA methylation. Most X-linked genes are subject to X-chromosome inactivation and only expressed from the active X chromosome. On the inactive X chromosome, the CpG island promoters of genes subject to X-chromosome inactivation are methylated in their promoter regions, while genes which escape from X- chromosome inactivation have unmethylated CpG island promoters on both the active and inactive X chromosomes. The first objective of this thesis was to determine if the DNA methylation of CpG island promoters could be used to accurately predict X chromosome inactivation status. The second objective was to use DNA methylation to predict X-chromosome inactivation status in a variety of tissues. A comparison of blood, muscle, kidney and neural tissues revealed tissue-specific X-chromosome inactivation, in which 12% of genes escaped from X-chromosome inactivation in some, but not all, tissues. X-linked DNA methylation analysis of placental tissues predicted four times higher escape from X-chromosome inactivation than in any other tissue. Despite the hypomethylation of repetitive elements on both the X chromosome and the autosomes, no changes were detected in the frequency or intensity of placental Cot-1 holes. -
Plenary and Platform Abstracts
American Society of Human Genetics 68th Annual Meeting PLENARY AND PLATFORM ABSTRACTS Abstract #'s Tuesday, October 16, 5:30-6:50 pm: 4. Featured Plenary Abstract Session I Hall C #1-#4 Wednesday, October 17, 9:00-10:00 am, Concurrent Platform Session A: 6. Variant Insights from Large Population Datasets Ballroom 20A #5-#8 7. GWAS in Combined Cancer Phenotypes Ballroom 20BC #9-#12 8. Genome-wide Epigenomics and Non-coding Variants Ballroom 20D #13-#16 9. Clonal Mosaicism in Cancer, Alzheimer's Disease, and Healthy Room 6A #17-#20 Tissue 10. Genetics of Behavioral Traits and Diseases Room 6B #21-#24 11. New Frontiers in Computational Genomics Room 6C #25-#28 12. Bone and Muscle: Identifying Causal Genes Room 6D #29-#32 13. Precision Medicine Initiatives: Outcomes and Lessons Learned Room 6E #33-#36 14. Environmental Exposures in Human Traits Room 6F #37-#40 Wednesday, October 17, 4:15-5:45 pm, Concurrent Platform Session B: 24. Variant Interpretation Practices and Resources Ballroom 20A #41-#46 25. Integrated Variant Analysis in Cancer Genomics Ballroom 20BC #47-#52 26. Gene Discovery and Functional Models of Neurological Disorders Ballroom 20D #53-#58 27. Whole Exome and Whole Genome Associations Room 6A #59-#64 28. Sequencing-based Diagnostics for Newborns and Infants Room 6B #65-#70 29. Omics Studies in Alzheimer's Disease Room 6C #71-#76 30. Cardiac, Valvular, and Vascular Disorders Room 6D #77-#82 31. Natural Selection and Human Phenotypes Room 6E #83-#88 32. Genetics of Cardiometabolic Traits Room 6F #89-#94 Wednesday, October 17, 6:00-7:00 pm, Concurrent Platform Session C: 33. -
Mouse Mid2 Conditional Knockout Project (CRISPR/Cas9)
https://www.alphaknockout.com Mouse Mid2 Conditional Knockout Project (CRISPR/Cas9) Objective: To create a Mid2 conditional knockout Mouse model (C57BL/6J) by CRISPR/Cas-mediated genome engineering. Strategy summary: The Mid2 gene (NCBI Reference Sequence: NM_011845 ; Ensembl: ENSMUSG00000000266 ) is located on Mouse chromosome X. 9 exons are identified, with the ATG start codon in exon 1 and the TAA stop codon in exon 9 (Transcript: ENSMUST00000112993). Exon 5 will be selected as conditional knockout region (cKO region). Deletion of this region should result in the loss of function of the Mouse Mid2 gene. To engineer the targeting vector, homologous arms and cKO region will be generated by PCR using BAC clone RP23-340F6 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 5 starts from about 49.34% of the coding region. The knockout of Exon 5 will result in frameshift of the gene. The size of intron 4 for 5'-loxP site insertion: 11103 bp, and the size of intron 5 for 3'-loxP site insertion: 1122 bp. The size of effective cKO region: ~628 bp. The cKO region does not have any other known gene. Page 1 of 7 https://www.alphaknockout.com Overview of the Targeting Strategy Wildtype allele gRNA region 5' gRNA region 3' 1 5 6 9 Targeting vector Targeted allele Constitutive KO allele (After Cre recombination) Legends Exon of mouse Mid2 Homology arm cKO region loxP site Page 2 of 7 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. -
Análise Integrativa De Perfis Transcricionais De Pacientes Com
UNIVERSIDADE DE SÃO PAULO FACULDADE DE MEDICINA DE RIBEIRÃO PRETO PROGRAMA DE PÓS-GRADUAÇÃO EM GENÉTICA ADRIANE FEIJÓ EVANGELISTA Análise integrativa de perfis transcricionais de pacientes com diabetes mellitus tipo 1, tipo 2 e gestacional, comparando-os com manifestações demográficas, clínicas, laboratoriais, fisiopatológicas e terapêuticas Ribeirão Preto – 2012 ADRIANE FEIJÓ EVANGELISTA Análise integrativa de perfis transcricionais de pacientes com diabetes mellitus tipo 1, tipo 2 e gestacional, comparando-os com manifestações demográficas, clínicas, laboratoriais, fisiopatológicas e terapêuticas Tese apresentada à Faculdade de Medicina de Ribeirão Preto da Universidade de São Paulo para obtenção do título de Doutor em Ciências. Área de Concentração: Genética Orientador: Prof. Dr. Eduardo Antonio Donadi Co-orientador: Prof. Dr. Geraldo A. S. Passos Ribeirão Preto – 2012 AUTORIZO A REPRODUÇÃO E DIVULGAÇÃO TOTAL OU PARCIAL DESTE TRABALHO, POR QUALQUER MEIO CONVENCIONAL OU ELETRÔNICO, PARA FINS DE ESTUDO E PESQUISA, DESDE QUE CITADA A FONTE. FICHA CATALOGRÁFICA Evangelista, Adriane Feijó Análise integrativa de perfis transcricionais de pacientes com diabetes mellitus tipo 1, tipo 2 e gestacional, comparando-os com manifestações demográficas, clínicas, laboratoriais, fisiopatológicas e terapêuticas. Ribeirão Preto, 2012 192p. Tese de Doutorado apresentada à Faculdade de Medicina de Ribeirão Preto da Universidade de São Paulo. Área de Concentração: Genética. Orientador: Donadi, Eduardo Antonio Co-orientador: Passos, Geraldo A. 1. Expressão gênica – microarrays 2. Análise bioinformática por module maps 3. Diabetes mellitus tipo 1 4. Diabetes mellitus tipo 2 5. Diabetes mellitus gestacional FOLHA DE APROVAÇÃO ADRIANE FEIJÓ EVANGELISTA Análise integrativa de perfis transcricionais de pacientes com diabetes mellitus tipo 1, tipo 2 e gestacional, comparando-os com manifestações demográficas, clínicas, laboratoriais, fisiopatológicas e terapêuticas. -
Supporting Information
Supporting Information Pouryahya et al. SI Text Table S1 presents genes with the highest absolute value of Ricci curvature. We expect these genes to have significant contribution to the network’s robustness. Notably, the top two genes are TP53 (tumor protein 53) and YWHAG gene. TP53, also known as p53, it is a well known tumor suppressor gene known as the "guardian of the genome“ given the essential role it plays in genetic stability and prevention of cancer formation (1, 2). Mutations in this gene play a role in all stages of malignant transformation including tumor initiation, promotion, aggressiveness, and metastasis (3). Mutations of this gene are present in more than 50% of human cancers, making it the most common genetic event in human cancer (4, 5). Namely, p53 mutations play roles in leukemia, breast cancer, CNS cancers, and lung cancers, among many others (6–9). The YWHAG gene encodes the 14-3-3 protein gamma, a member of the 14-3-3 family proteins which are involved in many biological processes including signal transduction regulation, cell cycle pro- gression, apoptosis, cell adhesion and migration (10, 11). Notably, increased expression of 14-3-3 family proteins, including protein gamma, have been observed in a number of human cancers including lung and colorectal cancers, among others, suggesting a potential role as tumor oncogenes (12, 13). Furthermore, there is evidence that loss Fig. S1. The histogram of scalar Ricci curvature of 8240 genes. Most of the genes have negative scalar Ricci curvature (75%). TP53 and YWHAG have notably low of p53 function may result in upregulation of 14-3-3γ in lung cancer Ricci curvatures. -
Molecular Analyses of Malignant Pleural Mesothelioma
Molecular Analyses of Malignant Pleural Mesothelioma Shir Kiong Lo National Heart and Lung Institute Imperial College Dovehouse Street London SW3 6LY A thesis submitted for MD (Res) Faculty of Medicine, Imperial College London 2016 1 Abstract Malignant pleural mesothelioma (MPM) is an aggressive cancer that is strongly associated with asbestos exposure. Majority of patients with MPM present with advanced disease and the treatment paradigm mainly involves palliative chemotherapy and best supportive care. The current chemotherapy options are limited and ineffective hence there is an urgent need to improve patient outcomes. This requires better understanding of the genetic alterations driving MPM to improve diagnostic, prognostic and therapeutic strategies. This research aims to gain further insights in the pathogenesis of MPM by exploring the tumour transcriptional and mutational profiles. We compared gene expression profiles of 25 MPM tumours and 5 non-malignant pleura. This revealed differentially expressed genes involved in cell migration, invasion, cell cycle and the immune system that contribute to the malignant phenotype of MPM. We then constructed MPM-associated co-expression networks using weighted gene correlation network analysis to identify clusters of highly correlated genes. These identified three distinct molecular subtypes of MPM associated with genes involved in WNT and TGF-ß signalling pathways. Our results also revealed genes involved in cell cycle control especially the mitotic phase correlated significantly with poor prognosis. Through exome analysis of seven paired tumour/blood and 29 tumour samples, we identified frequent mutations in BAP1 and NF2. Additionally, the mutational profile of MPM is enriched with genes encoding FAK, MAPK and WNT signalling pathways. -
Anti-COX7B Antibody
03/19 Anti-COX7B Antibody CATALOG NO.: A1756-100 100 μl. BACKGROUND DESCRIPTION: Cytochrome c oxidase (COX), the terminal component of the mitochondrial respiratory chain, catalyzes the electron transfer from reduced cytochrome c to oxygen. This component is a heteromeric complex consisting of 3 catalytic subunits encoded by mitochondrial genes and multiple structural subunits encoded by nuclear genes. The mitochondrial- encoded subunits function in electron transfer, and the nuclear-encoded subunits may function in the regulation and assembly of the complex. This nuclear gene encodes subunit VIIb, which is highly similar to bovine COX VIIb protein and is found in all tissues. This gene may have several pseudogenes on chromosomes 1, 2, 20 and 22. ALTERNATE NAMES: Cytochrome c oxidase polypeptide VIIb, Cytochrome c oxidase subunit 7B, Cytochrome c oxidase subunit 7B mitochondrial, APLCC. ANTIBODY TYPE: Polyclonal CONCENTRATION: 0.3 mg/ml HOST/ISOTYPE: Rabbit / IgG. IMMUNOGEN: Recombinant protein of human COX7B. MOLECULAR WEIGHT: 9 kDa. PURIFICATION: Affinity purification. FORM: Liquid. FORMULATION: PBS with 0.05% sodium azide, 50% glycerol, PH7.3 SPECIES REACTIVITY: Rat. Human. STORAGE CONDITIONS: Store at -20°C. Avoid freeze / thaw cycles. APPLICATIONS AND USAGE: WB 1:500-1:2000, IHC 1:50-1:200. : IHC staining of paraffin-embedded Human colon cancer using Anti-COX7B Antibody. 155 S. Milpitas Blvd., Milpitas, CA 95035 USA | T: (408)493-1800 F: (408)493-1801 | www.biovision.com | [email protected] 03/19 : Western Blot analysis of 293T cell using Anti-COX7B Antibody. RELATED PRODUCTS: Cox-3 Antibody (3687). Cyclooxygenase (COX) Activity Assay Kit (Fluorometric) (K549). TFPI Antibody (3379). -
COX7B Antibody
Product Datasheet COX7B Antibody Catalog No: #35581 Orders: [email protected] Description Support: [email protected] Product Name COX7B Antibody Host Species Rabbit Clonality Polyclonal Purification Antigen affinity purification. Applications WB IHC Species Reactivity Hu Specificity The antibody detects endogenous levels of total COX7B protein. Immunogen Type Recombinant Protein Immunogen Description Fusion protein corresponding to a region derived from internal residues of human Cytochrome c oxidase subunit VIIb Target Name COX7B Other Names APLCC Accession No. Swiss-Prot#: P24311NCBI Gene ID: 1349Gene Accssion: BC018386 SDS-PAGE MW 9kd Concentration 1.8mg/ml Formulation Rabbit IgG in pH7.4 PBS, 0.05% NaN3, 40% Glycerol. Storage Store at -20°C Application Details Western blotting: 1:500-1:2000 Immunohistochemistry: 1:50-1:200 Images Gel: 15%+10%SDS-PAGE Lysate: 50ug 293T cell Primary antibody: 1/700 dilution Secondary antibody dilution: 1/8000 Exposure time: 30 seconds Address: 8400 Baltimore Ave., Suite 302, College Park, MD 20740, USA http://www.sabbiotech.com 1 Immunohistochemical analysis of paraffin-embedded Human colon cancer tissue using #35581 at dilution 1/60. Background Cytochrome c oxidase (COX), the terminal component of the mitochondrial respiratory chain, catalyzes the electron transfer from reduced cytochrome c to oxygen. This component is a heteromeric complex consisting of 3 catalytic subunits encoded by mitochondrial genes and multiple structural subunits encoded by nuclear genes. The mitochondrially-encoded subunits function in electron transfer, and the nuclear-encoded subunits may function in the regulation and assembly of the complex. This nuclear gene encodes subunit VIIb, which is highly similar to bovine COX VIIb protein and is found in all tissues.