Varios autores han registrado la importancia de la metilación del gen IDS en el proceso de inactivación del cromosoma X. Adicionalmente, algunos pacientes con mucopolisacaridosis muestran un patrón de sesgo en la inactivación del cromosoma X y su relación con una disminución en la actividad de la iduronatosintasa 2. Nuestro estudio registra un patrón consistente de mutaciones de tipo transicional en este gen que podrían estar relacionadas con la génesis de mutaciones de tipo patológico, con el propósito de atenuar los efectos de una inactivación no aleatoria del cromosoma X. Se considera este hallazgo de particular importancia, ya que apoyaría la propuesta de un tamizaje de sitios de metilación en el cromosoma X en mujeres en edad fértil. Este tamizaje podría ayudar a disminuir las frecuencias alélicas de variantes relacionadas con un número variado de enfermedades asociadas al cromosoma X, como son: MPS tipo II, síndrome de Lesch-Nyhan y la distrofia muscular tipo Duchenne.
Fragile X-associated tremor/ataxia syndrome (FXTAS) is an inherited neurodegenerative disorder manifesting in carriers of 55 to 200 CGG repeats in the 5' untranslated region (UTR) of the fragile X mental retardation gene (FMR1). FXTAS is characterized by enhanced FMR1 transcription and the accumulation of CGG repeat-containing FMR1 messenger RNA in nuclear foci, while the FMRP protein expression levels remain normal or moderately low. The neuropathological hallmark in FXTAS is the presence of intranuclear, ubiquitin-positive inclusions that also contain FMR1 transcript. Yet, the complete protein complement of FXTAS inclusions and the molecular events that trigger neuronal death in FXTAS remain unclear. In this review, we present the two most accepted toxicity mechanisms described so far, namely RNA gain-of-function and protein gain-of-function by means of repeat-associated non-AUG translation, and discuss current experimental and computational strategies to better understand FXTAS pathogenesis. Finally, we review the current perspectives for drug development with disease-modifying potential for FXTAS. ; Our research received funding from the European Union Seventh Framework Programme (FP7/2007-2013), through the European Research Council, under grant agreement RIBOMYLOME_ 309545 (Gian Gaetano Tartaglia), and from the Fundació La Marató de TV3 (20142731). We also acknowledge support from the Spanish Ministry of Economy and Competitiveness (BFU2011-26206 and BFU2014-55054-P) and "Centro de Excelencia Severo Ochoa 2013– 2017" (SEV-2012-0208)
MA was funded by NIH NIAID grant AI134834 and by DOD Lupus grant W81XH-18-1-0635. Work in the lab of BP was funded by the Spanish Ministry of Science, Innovation and Universities (BFU2017-88407-P), the AXA Research Fund and the Agencia de Gestio d'Ajuts Universitaris i de Recerca (AGAUR, 2017 SGR 346). We would like to thank the Spanish Ministry of Economy, Industry and Competitiveness (MEIC) to the EMBL partnership and to the "Centro de Excelencia Severo Ochoa". We also acknowledge support of the CERCA Programme of the Generalitat de Catalunya. CM was supported by the Agence Nationale de la Recherche (ANR-14-CE10-0017, ANR-18-CE12-0017), the Ligue Contre le Cancer, the LabEx "Who Am I?" (ANR-11-LABX-0071), the Association pour la Recherche contre le Cancer (ARC), the Association Française contre les Myopathies (AFM) and by the Université de Paris IdEx (ANR-18-IDEX-0001) funded by the French Government through its "Investments for the Future" program
Fragile X-associated tremor/ataxia syndrome (FXTAS) is a late-onset neurodegenerative monogenetic disorder affecting carriers of premutation (PM) forms of the FMR1 gene, resulting in a progressive development of tremors, ataxia, and neuropsychological problems. This highly disabling disease is quite common in the general population with an estimation of about 20 million PM carriers worldwide. The chances of developing FXTAS increase dramatically with age, with about 45% of male carriers over the age of 50 being affected. Both the gene and pathogenic trigger, a mutant expansion of CGG RNA, causing FXTAS are known. This makes it an interesting disease to develop targeted therapeutic interventions for. Yet, no such interventions are available at this moment. Here we discuss in silico, in vitro, and in vivo approaches and how they have been used to identify the molecular determinants of FXTAS pathology. These approaches have yielded substantial information about FXTAS pathology and, consequently, many markers have emerged to play a key role in understanding the disease mechanism. Integration of the different approaches is expected to provide crucial information about the value of these markers as either therapeutic target or biomarker, essential to monitor therapeutic interventions in the future. ; The research leading to these results has been supported by the European Research Council under the European Union's Seventh Framework Programme (FP7/2007-2013) ERC grant agreement RIBOMYLOME_309545 to GT and ASTRA 855923 to GT, the Spanish Ministry of Science and Innovation (AEI/ERDF, BFU2014-55054-P and BFU2017-86970-P) and the 'Fundació La Marató de TV3' (PI043296)
Meta-analysis of epidemiological world-wide reports of SARS-CoV-2 patients requiring mechanical ventilation in intensive care units highlighted the male sex as a risk factor for severe, often fatal evolution of COVID-19 disease, as signaled by previous coronavirus infections. X chromosome inactivation (XCI), an epigenetic mechanism used by female somatic cells to equalize the dosage of X-linked genes between the sexes and the female advantage with mosaicism of the numerous immune-related genes and the increased expression of those escaping XCI determined a growing recognition of the unique biology of the X chromosome to account for females more robust immune response. In the wake of studies aimed at establishing the contribution of immune-regulatory X-linked genes to sex-specific differences of COVID-19 disease, the expression of TLR7, a gene of innate immune response encoding a member of Toll-like family receptors sensing the SARS-CoV-2 endosomal RNA, has been quantified in human female plasmacytoid dendritic cells which are high producers of interferons, acting as powerful viral inhibitors. The study confirmed that TLR7 escapes XCI promoting higher TLR7 mRNA and higher interferon mRNA at the single-cell level. The relevance of TLR7 signaling has been highlighted by a Dutch study exploring the presence of genetic variants among young men with severe COVID-19 which identified pathogenic TLR7 variants in two pairs of brothers (mean age 26 years) without medical history admitted to intensive care units due to SARS-CoV-2 acute respiratory syndrome, one of whom deceased due to septic shock. Whole exome sequencing of the patients identified "loss of function variants" of the X-chromosomal TLR7 and functional studies on their peripheral blood mononucleate cells after in vitro stimulation with a TLR7 agonist showed significant reduction of TLR7-specific mRNA and decreased mRNA expression of various interferon type I genes as compared to family members and controls. While rare mutations in TLR7 are unlikely to be a major drive of severe COVID-19 disease, their identification begins to unravel the molecular underpinning of COVID-19 infection highlighting TLR7 receptor as a critical node in recognizing SARS-CoV-2 and initiating an early immune response to clear the virus and prevent the development of COVID-19.
Genome-wide association studies (GWAS) are not fully comprehensive, as current strategies typically test only the additive model, exclude the X chromosome, and use only one reference panel for genotype imputation. We implement an extensive GWAS strategy, GUIDANCE, which improves genotype imputation by using multiple reference panels and includes the analysis of the X chromosome and non-additive models to test for association. We apply this methodology to 62,281 subjects across 22 age-related diseases and identify 94 genome-wide associated loci, including 26 previously unreported. Moreover, we observe that 27.7% of the 94 loci are missed if we use standard imputation strategies with a single reference panel, such as HRC, and only test the additive model. Among the new findings, we identify three novel low-frequency recessive variants with odds ratios larger than 4, which need at least a three-fold larger sample size to be detected under the additive model. This study highlights the benefits of applying innovative strategies to better uncover the genetic architecture of complex diseases. ; This work has been sponsored by the grant SEV-2011-00067 and SEV2015-0493 of Severo Ochoa Program, awarded by the Spanish Government, by the grant TIN2015- 65316-P, awarded by the Spanish Ministry of Science and Innovation, and by the Generalitat de Catalunya (contract 2014-SGR-1051). This work was supported by an EFSD/Lilly research fellowship. Josep M. Mercader was supported by a Sara Borrell Fellowship from the Instituto Carlos III, Beatriu de Pinós fellowship from the Agency for Management of University and Research Grants (AGAUR) and by the American Diabetes Association Innovative and Clinical Translational Award 1-19-ICTS-068. Sílvia Bonàs was supported by FI-DGR Fellowship from FIDGR 2013 from Agència de Gestió d'Ajuts Universitaris i de Recerca (AGAUR, Generalitat de Catalunya), and a 'Juan de la Cierva' postdoctoral fellowship (MINECO;FJCI-2017-32090). Cecilia Salvoro received funding from the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement H2020-MSCA-COFUND-2016- 754433. Cristian Ramon-Cortes pre-doctoral contract is financed by the Spanish Ministry of Science, Innovation, and Universities under contract BES-2016-076791. Elizabeth G. Atkinson was supported by the National Institutes of Mental Health (grants K01MH121659 and T32MH017119). Jose Florez was supported by NIH/NIDDK award K24 DK110550. This study made use of data generated by the UK10K Consortium, derived from samples from UK10K COHORT IMPUTATION (EGAS00001000713). A full list of the investigators who contributed to the generation of the data is available at www.UK10K.org. Funding for UK10K was provided by the Wellcome Trust under award WT091310. This study made use of data generated by the 'Genome of the Netherlands' project, which is funded by the Netherlands Organization for Scientific Research (grant no. 184021007). The data were made available as a Rainbow Project of BBMRI-NL. Samples were contributed by LifeLines (http://lifelines.nl/lifelines-research/general), the Leiden Longevity Study (http://www.healthy-ageing.nl; http://www.langleven.net), the Netherlands Twin Registry (NTR: http://www.tweelingenregister.org), the Rotterdam studies (http://www.erasmus-epidemiology.nl/rotterdamstudy) and the Genetic Research in Isolated Populations program (http://www.epib.nl/research/geneticepi/research. html#gip). The sequencing was carried out in collaboration with the Beijing Institute for Genomics (BGI). This study also made use of data generated by The Haplotype Reference Consortium (HRC) accessed through The European Genome-phenome Archive at the European Bioinformatics Institute with the accession numbers EGAD00001002729, after a form agreed by the Barcelona Supercomputing Center (BSC) with WTSI. This research has been conducted using also the UK Biobank Resource (application number 31063 and 27892). The Genotype-Tissue Expression (GTEx) Project was supported by the Common Fund of the Office of the Director of the National Institutes of Health, and by NCI, NHGRI, NHLBI, NIDA, NIMH, and NINDS. The data used for the analyses described in this manuscript were obtained from the GTEx Portal on 07/16/2019. We acknowledge PRACE for awarding us access to both MareNostrum supercomputer from the Barcelona Supercomputing Center, based in Spain at Barcelona, and the SuperMUC supercomputer of the Leibniz Supercomputing Center (LRZ), based in Garching at Germany (proposals numbers 2016143358 and 2016163985). The technical support group from the Barcelona Supercomputing Center is gratefully acknowledged. Finally, we thank all the Computational Genomics group at the BSC for their helpful discussions and valuable comments on the manuscript. We also acknowledge Elias Rodriguez Fos for designing the GUIDANCE logo. ; Peer Reviewed ; Article signat per 22 autors/autores: Marta Guindo-Martínez 1,18; Ramon Amela 1,18; Silvia Bonàs-Guarch 1,2,3; Montserrat Puiggròs 1; Cecilia Salvoro 1; Irene Miguel-Escalada 1,2,3; Caitlin E. Carey 4,5; Joanne B. Cole 6,7,8,9; Sina Rüeger 10; Elizabeth Atkinson 4,5,11; Aaron Leong 8,12; Friman Sanchez 1; Cristian Ramon-Cortes 1; Jorge Ejarque 1; Duncan S. Palmer 4,5,17; Mitja Kurki 10; FinnGen Consortium*, Krishna Aragam 11,13,14; Jose C. Florez 6,7,15; Rosa M. Badia 1; Josep M. Mercader 1,6,7,15,19✉ & David Torrents 1,16,19✉ *A full list of members and their affiliations appears in the Supplementary Information 1 Barcelona Supercomputing Center (BSC), Barcelona, Spain. 2 Regulatory Genomics and Diabetes, Centre for Genomic Regulation, The Barcelona Institute of Science and Technology, Barcelona, Spain. 3 CIBER de Diabetes y Enfermedades Metabólicas Asociadas, Madrid, Spain. 4 Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA. 5 Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA. 6 Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA. 7 Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA. 8 Harvard Medical School, Boston, MA, USA. 9 Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Boston, MA, USA. 10 Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland. 11 Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA. 12 Department of Medicine, Massachusetts General Hospital, Boston, MA, USA. 13 Cardiology Division, Massachusetts General Hospital, Boston, MA, USA. 14 Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA. 15 Department of Medicine, Harvard Medical School, Boston, MA, USA. 16 Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain. 17 Present address: GENOMICS plc, Oxford, UK. 18 These authors contributed equally: Marta Guindo-Martínez, Ramon Amela. 19 These authors jointly supervised this work: Josep M. Mercader, David Torrents. ; Postprint (published version)
Con el fin de purificar el ADN genómico del fitoplasma que afecta a los Urapanes de Bogotá, se realizó introducción de fitoplasmas, utilizando la ectoparásita Cúscuta subinclusa, a plantas jóvenes de Urapán, a partir de árboles sintomáticos de fitoplasmosis presentes en la Universidad Militar. La presencia de fitoplasmas fue confirmada en 14 de los 16 Urapanes receptores por medio del test DAPI. Solamente el 12.5% de los Urapanes receptores fue positivo por reacción en cadena de la polimerasa (PCR), con el par de primers universales para fitoplasmas R16F2n/R16R2. El producto de PCR obtenido a partir de amplificados de ADN de urapanes receptores con los primers R16F2n/R16R2 fue secuenciado y el análisis de la secuencia mostró similaridad entre el 99% y el 100% con fitoplasmas de distintos tipos. Se realizaron ensayos de Electroforesis de Campo Pulsado (ECP), con los sintomáticos de fitoplasmosis, pero no se obtuvieron bandas a pesar de que se utilizaron grandes cantidades de tejido. Con base en los resultados obtenidos en las pruebas moleculares, se concluyó que las plantas jóvenes de Urapán no son un buen reservorio para el aislamiento de ADN genómico de fitoplasmas. Se realizó introducción de fitoplasmas a plantas de Apio a partir de los Urapanes sintomáticos de la Universidad Militar, para tratar de encontrar un nuevo reservorio para el aislamiento de ADN genómico de fitoplasmas. Los Las plantas de apio infectadas resultaron positivas por PCR con el par de primers universales para fitoplasmas PhyRNAF3.3/R16R2. En los ensayos de ECP con Apio se obtuvieron bandas de aproximadamente 1125 Kb que se purificaron y se amplificaron por PCR con los primers PhyRNAF3.3/R16R2. El producto obtenido se mandó a secuenciar y se obtuvo similaridad del 99% con secuencias de tipo "Ash Yellows", incluidas dos secuencias reportadas en 2004 por el grupo de Biotecnología Vegetal de la Universidad Militar.
