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Piergiorge RM, da Silva Francisco Junior R, de Vasconcelos ATR, Santos-Rebouças CB. Multi-layered transcriptomic analysis reveals a pivotal role of FMR1 and other developmental genes in Alzheimer's disease-associated brain ceRNA network. Comput Biol Med 2023; 166:107494. [PMID: 37769462 DOI: 10.1016/j.compbiomed.2023.107494] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 09/05/2023] [Accepted: 09/15/2023] [Indexed: 09/30/2023]
Abstract
Alzheimer's disease (AD) is an increasingly neurodegenerative disorder that causes progressive cognitive decline and memory impairment. Despite extensive research, the underlying causes of late-onset AD (LOAD) are still in progress. This study aimed to establish a network of competing regulatory interactions involving circular RNAs (circRNAs), microRNAs (miRNAs), RNA-binding proteins (RBPs), and messenger RNAs (mRNAs) connected to LOAD. A systematic analysis of publicly available expression data was conducted to identify integrated differentially expressed genes (DEGs) from the hippocampus of LOAD patients. Subsequently, gene co-expression analysis identified modules comprising highly expressed DEGs that act cooperatively. The competition between co-expressed DEGs and miRNAs/RBPs and the simultaneous interactions between circRNA and miRNA/RBP revealed a complex ceRNA network responsible for post-transcriptional regulation in LOAD. Hippocampal expression data for miRNAs, circRNAs, and RBPs were used to filter relevant relationships for AD. An integrated topological score was used to identify the highly connected hub gene, from which a brain core ceRNA subnetwork was generated. The Fragile X Messenger Ribonucleoprotein 1 (FMR1) coding for the RBP FMRP emerged as the prominent driver gene in this subnetwork. FMRP has been previously related to AD but not in a ceRNA network context. Also, the substantial number of neurodevelopmental genes in the ceRNA subnetwork and their related biological pathways strengthen that AD shares common pathological mechanisms with developmental conditions. Our results enhance the current knowledge about the convergent ceRNA regulatory pathways underlying AD and provide potential targets for identifying early biomarkers and developing novel therapeutic interventions.
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Affiliation(s)
- Rafael Mina Piergiorge
- Department of Genetics, Institute of Biology Roberto Alcantara Gomes, State University of Rio de Janeiro, Rio de Janeiro, Brazil
| | | | | | - Cíntia Barros Santos-Rebouças
- Department of Genetics, Institute of Biology Roberto Alcantara Gomes, State University of Rio de Janeiro, Rio de Janeiro, Brazil.
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Ferreira CS, Francisco Junior RDS, Gerber AL, Guimarães APDC, de Carvalho FAA, Dos Reis BCS, Pinto-Mariz F, de Souza MS, de Vasconcelos ZFM, Goudouris ES, Vasconcelos ATR. Genetic screening in a Brazilian cohort with inborn errors of immunity. BMC Genom Data 2023; 24:47. [PMID: 37592284 PMCID: PMC10433585 DOI: 10.1186/s12863-023-01148-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Accepted: 08/07/2023] [Indexed: 08/19/2023] Open
Abstract
BACKGROUND Inherited genetic defects in immune system-related genes can result in Inborn Errors of Immunity (IEI), also known as Primary Immunodeficiencies (PID). Diagnosis of IEI disorders is challenging due to overlapping clinical manifestations. Accurate identification of disease-causing germline variants is crucial for appropriate treatment, prognosis, and genetic counseling. However, genetic sequencing is challenging in low-income countries like Brazil. This study aimed to perform genetic screening on patients treated within Brazil's public Unified Health System to identify candidate genetic variants associated with the patient's phenotype. METHODS Thirteen singleton unrelated patients from three hospitals in Rio de Janeiro were enrolled in this study. Genomic DNA was extracted from the peripheral blood lymphocytes of each patient, and whole exome sequencing (WES) analyses were conducted using Illumina NextSeq. Germline genetic variants in IEI-related genes were prioritized using a computational framework considering their molecular consequence in coding regions; minor allele frequency ≤ 0.01; pathogenicity classification based on American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) guidelines gathered from the VarSome clinical database; and IEI-related phenotype using the Franklin tool. The genes classification into IEI categories follows internationally recognized guidelines informed by the International Union of Immunological Societies Expert Committee. Additional methods for confirmation of the variant included Sanger sequencing, phasing analysis, and splice site prediction. RESULTS A total of 16 disease-causing variants in nine genes, encompassing six different IEI categories, were identified. X-Linked Agammaglobulinemia, caused by BTK variations, emerged as the most prevalent IEI disorder in the cohort. However, pathogenic and likely pathogenic variants were also reported in other known IEI-related genes, namely CD40LG, CARD11, WAS, CYBB, C6, and LRBA. Interestingly, two patients with suspected IEI exhibited pathogenic variants in non-IEI-related genes, ABCA12 and SLC25A13, potentially explaining their phenotypes. CONCLUSIONS Genetic screening through WES enabled the detection of potentially harmful variants associated with IEI disorders. These findings contribute to a better understanding of patients' clinical manifestations by elucidating the genetic basis underlying their phenotypes.
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Affiliation(s)
- Cristina Santos Ferreira
- Bioinformatics Laboratory-LABINFO, National Laboratory of Scientific Computation LNCC/MCTIC, Av. Getúlio Vargas, 333, Quitandinha CEP: 25651-075, Petrópolis, Rio de Janeiro, Brazil
| | - Ronaldo da Silva Francisco Junior
- Bioinformatics Laboratory-LABINFO, National Laboratory of Scientific Computation LNCC/MCTIC, Av. Getúlio Vargas, 333, Quitandinha CEP: 25651-075, Petrópolis, Rio de Janeiro, Brazil
| | - Alexandra Lehmkuhl Gerber
- Bioinformatics Laboratory-LABINFO, National Laboratory of Scientific Computation LNCC/MCTIC, Av. Getúlio Vargas, 333, Quitandinha CEP: 25651-075, Petrópolis, Rio de Janeiro, Brazil
| | - Ana Paula de Campos Guimarães
- Bioinformatics Laboratory-LABINFO, National Laboratory of Scientific Computation LNCC/MCTIC, Av. Getúlio Vargas, 333, Quitandinha CEP: 25651-075, Petrópolis, Rio de Janeiro, Brazil
| | - Flavia Amendola Anisio de Carvalho
- Allergy and Immunology Service of Institute of Women, Children and Adolescents' Health Fernandes Figueira (IFF/FIOCRUZ), Rio de Janeiro, RJ, Brazil
| | - Bárbara Carvalho Santos Dos Reis
- Allergy and Immunology Service of Institute of Women, Children and Adolescents' Health Fernandes Figueira (IFF/FIOCRUZ), Rio de Janeiro, RJ, Brazil
| | - Fernanda Pinto-Mariz
- Allergy and Immunology Service of the Martagão Gesteira Institute for Childcare and Pediatrics (IPPMG) - Federal University of Rio de Janeiro (UFRJ), Rio de Janeiro, RJ, Brazil
| | - Monica Soares de Souza
- Allergy and Immunology Sector of the Pediatric Service of the Federal Hospital of Rio de Janeiro State (HFSE) - Ministry of Health, Rio de Janeiro, RJ, Brazil
| | - Zilton Farias Meira de Vasconcelos
- Laboratory of High Complexity of the Institute of Women, Children and Adolescents' Health Fernandes Figueira (IFF/FIOCRUZ), Rio de Janeiro, RJ, Brazil
| | - Ekaterini Simões Goudouris
- Allergy and Immunology Service of the Martagão Gesteira Institute for Childcare and Pediatrics (IPPMG) - Federal University of Rio de Janeiro (UFRJ), Rio de Janeiro, RJ, Brazil
| | - Ana Tereza Ribeiro Vasconcelos
- Bioinformatics Laboratory-LABINFO, National Laboratory of Scientific Computation LNCC/MCTIC, Av. Getúlio Vargas, 333, Quitandinha CEP: 25651-075, Petrópolis, Rio de Janeiro, Brazil.
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Ferreira CS, da Silva Francisco Junior R, Gerber AL, Guimarães APDC, Amendola FA, Pinto-Mariz F, de Souza MS, Miranda PCB, de Vasconcelos ZFM, Goudouris ES, Vasconcelos ATR. Assessing whole-exome sequencing data from undiagnosed Brazilian patients to improve the diagnostic yield of inborn errors of immunity. BMC Genom Data 2023; 24:36. [PMID: 37391719 PMCID: PMC10314602 DOI: 10.1186/s12863-023-01137-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Accepted: 06/19/2023] [Indexed: 07/02/2023] Open
Abstract
OBJECTIVES Inborn error of immunity (IEI) comprises a broad group of inherited immunological disorders that usually display an overlap in many clinical manifestations challenging their diagnosis. The identification of disease-causing variants from whole-exome sequencing (WES) data comprises the gold-standard approach to ascertain IEI diagnosis. The efforts to increase the availability of clinically relevant genomic data for these disorders constitute an important improvement in the study of rare genetic disorders. This work aims to make available WES data of Brazilian patients' suspicion of IEI without a genetic diagnosis. We foresee a broad use of this dataset by the scientific community in order to provide a more accurate diagnosis of IEI disorders. DATA DESCRIPTION Twenty singleton unrelated patients treated at four different hospitals in the state of Rio de Janeiro, Brazil were enrolled in our study. Half of the patients were male with mean ages of 9 ± 3, while females were 12 ± 10 years old. The WES was performed in the Illumina NextSeq platform with at least 90% of sequenced bases with a minimum of 30 reads depth. Each sample had an average of 20,274 variants, comprising 116 classified as rare pathogenic or likely pathogenic according to American College of Medical Genetics and Genomics and the Association (ACMG) guidelines. The genotype-phenotype association was impaired by the lack of detailed clinical and laboratory information, besides the unavailability of molecular and functional studies which, comprise the limitations of this study. Overall, the access to clinical exome sequencing data is limited, challenging exploratory analyses and the understanding of genetic mechanisms underlying disorders. Therefore, by making these data available, we aim to increase the number of WES data from Brazilian samples despite contributing to the study of monogenic IEI-disorders.
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Affiliation(s)
- Cristina Santos Ferreira
- Bioinformatics Laboratory-LABINFO, National Laboratory of Scientific Computation LNCC/MCTIC, Av. Getúlio Vargas, 333, Quitandinha, Petrópolis, Rio de Janeiro, 25651-075, Brazil
| | - Ronaldo da Silva Francisco Junior
- Bioinformatics Laboratory-LABINFO, National Laboratory of Scientific Computation LNCC/MCTIC, Av. Getúlio Vargas, 333, Quitandinha, Petrópolis, Rio de Janeiro, 25651-075, Brazil
| | - Alexandra Lehmkuhl Gerber
- Bioinformatics Laboratory-LABINFO, National Laboratory of Scientific Computation LNCC/MCTIC, Av. Getúlio Vargas, 333, Quitandinha, Petrópolis, Rio de Janeiro, 25651-075, Brazil
| | - Ana Paula de Campos Guimarães
- Bioinformatics Laboratory-LABINFO, National Laboratory of Scientific Computation LNCC/MCTIC, Av. Getúlio Vargas, 333, Quitandinha, Petrópolis, Rio de Janeiro, 25651-075, Brazil
| | - Flávia Anisio Amendola
- Allergy and Immunology Service of Institute of Women, Children and Adolescents' Health Fernandes Figueira (IFF) - Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro, RJ, Brazil
| | - Fernanda Pinto-Mariz
- Allergy and Immunology Service of the Martagão Gesteira Institute for Childcare and Pediatrics (IPPMG), Federal University of Rio de Janeiro (UFRJ), Rio de Janeiro-RJ, Brazil
| | | | | | - Zilton Farias Meira de Vasconcelos
- Laboratory of High Complexity of the Institute of Women, Children and Adolescents' Health Fernandes Figueira (IFF) - Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro, RJ, Brazil
| | - Ekaterini Simões Goudouris
- Allergy and Immunology Service of the Martagão Gesteira Institute for Childcare and Pediatrics (IPPMG), Federal University of Rio de Janeiro (UFRJ), Rio de Janeiro-RJ, Brazil
| | - Ana Tereza Ribeiro Vasconcelos
- Bioinformatics Laboratory-LABINFO, National Laboratory of Scientific Computation LNCC/MCTIC, Av. Getúlio Vargas, 333, Quitandinha, Petrópolis, Rio de Janeiro, 25651-075, Brazil.
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Francisco Junior RDS, de Almeida LGP, Lamarca AP, Cavalcante L, Martins Y, Gerber AL, Guimarães APDC, Salviano RB, Dos Santos FL, de Oliveira TH, de Souza IV, de Carvalho EM, Ribeiro MS, Carvalho S, da Silva FD, Garcia MHDO, de Souza LM, da Silva CG, Ribeiro CLP, Cavalcanti AC, de Mello CMB, Tanuri A, Vasconcelos ATR. Emergence of Within-Host SARS-CoV-2 Recombinant Genome After Coinfection by Gamma and Delta Variants: A Case Report. Front Public Health 2022; 10:849978. [PMID: 35273945 PMCID: PMC8902039 DOI: 10.3389/fpubh.2022.849978] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Accepted: 01/24/2022] [Indexed: 12/13/2022] Open
Abstract
In this study, we report the first case of intra-host SARS-CoV-2 recombination during a coinfection by the variants of concern (VOC) AY.33 (Delta) and P.1 (Gamma) supported by sequencing reads harboring a mosaic of lineage-defining mutations. By using next-generation sequencing reads intersecting regions that simultaneously overlap lineage-defining mutations from Gamma and Delta, we were able to identify a total of six recombinant regions across the SARS-CoV-2 genome within a sample. Four of them mapped in the spike gene and two in the nucleocapsid gene. We detected mosaic reads harboring a combination of lineage-defining mutations from each VOC. To our knowledge, this is the first report of intra-host RNA-RNA recombination between two lineages of SARS-CoV-2, which can represent a threat to public health management during the COVID-19 pandemic due to the possibility of the emergence of viruses with recombinant phenotypes.
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Affiliation(s)
| | - Luiz G P de Almeida
- Laboratório de Bioinformática, Laboratório Nacional de Computação Científica, Petrópolis, Brazil
| | - Alessandra P Lamarca
- Laboratório de Bioinformática, Laboratório Nacional de Computação Científica, Petrópolis, Brazil
| | - Liliane Cavalcante
- Laboratório de Bioinformática, Laboratório Nacional de Computação Científica, Petrópolis, Brazil
| | - Yasmmin Martins
- Laboratório de Bioinformática, Laboratório Nacional de Computação Científica, Petrópolis, Brazil
| | - Alexandra L Gerber
- Laboratório de Bioinformática, Laboratório Nacional de Computação Científica, Petrópolis, Brazil
| | - Ana Paula de C Guimarães
- Laboratório de Bioinformática, Laboratório Nacional de Computação Científica, Petrópolis, Brazil
| | - Ricardo Barbosa Salviano
- Departamento de Genética, Instituto de Biologia, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | - Fernanda Leitão Dos Santos
- Departamento de Genética, Instituto de Biologia, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | - Thiago Henrique de Oliveira
- Departamento de Genética, Instituto de Biologia, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | | | | | | | - Silvia Carvalho
- Secretaria Estadual de Saúde do Rio de Janeiro, Rio de Janeiro, Brazil
| | | | | | | | | | | | | | | | - Amilcar Tanuri
- Departamento de Genética, Instituto de Biologia, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | - Ana Tereza R Vasconcelos
- Laboratório de Bioinformática, Laboratório Nacional de Computação Científica, Petrópolis, Brazil
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Francisco Junior RDS, Temerozo JR, Ferreira CDS, Martins Y, Souza TML, Medina-Acosta E, de Vasconcelos ATR. Differential haplotype expression in class I MHC genes during SARS-CoV-2 infection of human lung cell lines. Front Immunol 2022; 13:1101526. [PMID: 36818472 PMCID: PMC9929942 DOI: 10.3389/fimmu.2022.1101526] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Accepted: 12/19/2022] [Indexed: 02/05/2023] Open
Abstract
Introduction Cell entry of SARS-CoV-2 causes genome-wide disruption of the transcriptional profiles of genes and biological pathways involved in the pathogenesis of COVID-19. Expression allelic imbalance is characterized by a deviation from the Mendelian expected 1:1 expression ratio and is an important source of allele-specific heterogeneity. Expression allelic imbalance can be measured by allele-specific expression analysis (ASE) across heterozygous informative expressed single nucleotide variants (eSNVs). ASE reflects many regulatory biological phenomena that can be assessed by combining genome and transcriptome information. ASE contributes to the interindividual variability associated with the disease. We aim to estimate the transcriptome-wide impact of SARS-CoV-2 infection by analyzing eSNVs. Methods We compared ASE profiles in the human lung cell lines Calu-3, A459, and H522 before and after infection with SARS-CoV-2 using RNA-Seq experiments. Results We identified 34 differential ASE (DASE) sites in 13 genes (HLA-A, HLA-B, HLA-C, BRD2, EHD2, GFM2, GSPT1, HAVCR1, MAT2A, NQO2, SUPT6H, TNFRSF11A, UMPS), all of which are enriched in protein binding functions and play a role in COVID-19. Most DASE sites were assigned to the MHC class I locus and were predominantly upregulated upon infection. DASE sites in the MHC class I locus also occur in iPSC-derived airway epithelium basal cells infected with SARS-CoV-2. Using an RNA-Seq haplotype reconstruction approach, we found DASE sites and adjacent eSNVs in phase (i.e., predicted on the same DNA strand), demonstrating differential haplotype expression upon infection. We found a bias towards the expression of the HLA alleles with a higher binding affinity to SARS-CoV-2 epitopes. Discussion Independent of gene expression compensation, SARS-CoV-2 infection of human lung cell lines induces transcriptional allelic switching at the MHC loci. This suggests a response mechanism to SARS-CoV-2 infection that swaps HLA alleles with poor epitope binding affinity, an expectation supported by publicly available proteome data.
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Affiliation(s)
| | - Jairo R Temerozo
- Laboratory on Thymus Research, Oswaldo Cruz Institute (Fiocruz), Rio de Janeiro, Brazil.,National Institute of Science and Technology on Neuroimmunomodulation, Rio de Janeiro, Brazil
| | - Cristina Dos Santos Ferreira
- Bioinformatics Laboratory (LABINFO), National Laboratory of Scientific Computation (LNCC/MCTIC), Petrópolis, Brazil
| | - Yasmmin Martins
- Instituto de Cálculo, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires (FCEyN-UBA), Buenos Aires, Argentina
| | - Thiago Moreno L Souza
- Laboratory of Immunopharmacology, Oswaldo Cruz Institute (IOC), Oswaldo Cruz Foundation (Fiocruz), Rio de Janeiro, Brazil.,Center for Technological Development in Health (CDTS), National Institute for Science and Technology on Innovation on Neglected Diseases Neglected Populations (INCT/IDNP), Oswaldo Cruz Foundation (Fiocruz), Rio de Janeiro, Brazil
| | - Enrique Medina-Acosta
- Molecular Identification and Diagnostics Unit (NUDIM), Laboratory of Biotechnology, Center for Biosciences and Biotechnology, Universidade Estadual do Norte Fluminense Darcy Ribeiro (UENF), Campos dos Goytacazes, Brazil
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da Silva Francisco Junior R, Lamarca AP, de Almeida LGP, Cavalcante L, Machado DT, Martins Y, Brustolini O, Gerber AL, de C Guimarães AP, Gonçalves RB, Alves C, Mariani D, Cruz TF, de Souza IV, de Carvalho EM, Ribeiro MS, Carvalho S, da Silva FD, de Oliveira Garcia MH, de Souza LM, da Silva CG, Ribeiro CLP, Cavalcanti AC, de Mello CMB, Struchiner CJ, Tanuri A, Vasconcelos ATR. Turnover of SARS-CoV-2 Lineages Shaped the Pandemic and Enabled the Emergence of New Variants in the State of Rio de Janeiro, Brazil. Viruses 2021; 13:2013. [PMID: 34696443 PMCID: PMC8537965 DOI: 10.3390/v13102013] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Revised: 09/23/2021] [Accepted: 09/29/2021] [Indexed: 01/02/2023] Open
Abstract
In the present study, we provide a retrospective genomic epidemiology analysis of the SARS-CoV-2 pandemic in the state of Rio de Janeiro, Brazil. We gathered publicly available data from GISAID and sequenced 1927 new genomes sampled periodically from March 2021 to June 2021 from 91 out of the 92 cities of the state. Our results showed that the pandemic was characterized by three different phases driven by a successive replacement of lineages. Interestingly, we noticed that viral supercarriers accounted for the overwhelming majority of the circulating virus (>90%) among symptomatic individuals in the state. Moreover, SARS-CoV-2 genomic surveillance also revealed the emergence and spread of two new variants (P.5 and P.1.2), firstly reported in this study. Our findings provided important lessons learned from the different epidemiological aspects of the SARS-CoV-2 dynamic in Rio de Janeiro. Altogether, this might have a strong potential to shape future decisions aiming to improve public health management and understanding mechanisms underlying virus dispersion.
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Affiliation(s)
- Ronaldo da Silva Francisco Junior
- Laboratório de Bioinformática, Laboratório Nacional de Computação Científica, Petrópolis 25651-076, Brazil; (R.d.S.F.J.); (A.P.L.); (L.G.P.d.A.); (L.C.); (D.T.M.); (Y.M.); (O.B.); (A.L.G.); (A.P.d.C.G.); (R.B.G.)
| | - Alessandra P Lamarca
- Laboratório de Bioinformática, Laboratório Nacional de Computação Científica, Petrópolis 25651-076, Brazil; (R.d.S.F.J.); (A.P.L.); (L.G.P.d.A.); (L.C.); (D.T.M.); (Y.M.); (O.B.); (A.L.G.); (A.P.d.C.G.); (R.B.G.)
| | - Luiz G P de Almeida
- Laboratório de Bioinformática, Laboratório Nacional de Computação Científica, Petrópolis 25651-076, Brazil; (R.d.S.F.J.); (A.P.L.); (L.G.P.d.A.); (L.C.); (D.T.M.); (Y.M.); (O.B.); (A.L.G.); (A.P.d.C.G.); (R.B.G.)
| | - Liliane Cavalcante
- Laboratório de Bioinformática, Laboratório Nacional de Computação Científica, Petrópolis 25651-076, Brazil; (R.d.S.F.J.); (A.P.L.); (L.G.P.d.A.); (L.C.); (D.T.M.); (Y.M.); (O.B.); (A.L.G.); (A.P.d.C.G.); (R.B.G.)
| | - Douglas Terra Machado
- Laboratório de Bioinformática, Laboratório Nacional de Computação Científica, Petrópolis 25651-076, Brazil; (R.d.S.F.J.); (A.P.L.); (L.G.P.d.A.); (L.C.); (D.T.M.); (Y.M.); (O.B.); (A.L.G.); (A.P.d.C.G.); (R.B.G.)
| | - Yasmmin Martins
- Laboratório de Bioinformática, Laboratório Nacional de Computação Científica, Petrópolis 25651-076, Brazil; (R.d.S.F.J.); (A.P.L.); (L.G.P.d.A.); (L.C.); (D.T.M.); (Y.M.); (O.B.); (A.L.G.); (A.P.d.C.G.); (R.B.G.)
| | - Otávio Brustolini
- Laboratório de Bioinformática, Laboratório Nacional de Computação Científica, Petrópolis 25651-076, Brazil; (R.d.S.F.J.); (A.P.L.); (L.G.P.d.A.); (L.C.); (D.T.M.); (Y.M.); (O.B.); (A.L.G.); (A.P.d.C.G.); (R.B.G.)
| | - Alexandra L Gerber
- Laboratório de Bioinformática, Laboratório Nacional de Computação Científica, Petrópolis 25651-076, Brazil; (R.d.S.F.J.); (A.P.L.); (L.G.P.d.A.); (L.C.); (D.T.M.); (Y.M.); (O.B.); (A.L.G.); (A.P.d.C.G.); (R.B.G.)
| | - Ana Paula de C Guimarães
- Laboratório de Bioinformática, Laboratório Nacional de Computação Científica, Petrópolis 25651-076, Brazil; (R.d.S.F.J.); (A.P.L.); (L.G.P.d.A.); (L.C.); (D.T.M.); (Y.M.); (O.B.); (A.L.G.); (A.P.d.C.G.); (R.B.G.)
| | - Reinaldo Bellini Gonçalves
- Laboratório de Bioinformática, Laboratório Nacional de Computação Científica, Petrópolis 25651-076, Brazil; (R.d.S.F.J.); (A.P.L.); (L.G.P.d.A.); (L.C.); (D.T.M.); (Y.M.); (O.B.); (A.L.G.); (A.P.d.C.G.); (R.B.G.)
| | - Cassia Alves
- Departamento de Genética, Instituto de Biologia, Universidade Federal do Rio de Janeiro, Rio de Janeiro 21941-570, Brazil; (C.A.); (D.M.); (T.F.C.); (A.T.)
| | - Diana Mariani
- Departamento de Genética, Instituto de Biologia, Universidade Federal do Rio de Janeiro, Rio de Janeiro 21941-570, Brazil; (C.A.); (D.M.); (T.F.C.); (A.T.)
| | - Thais Felix Cruz
- Departamento de Genética, Instituto de Biologia, Universidade Federal do Rio de Janeiro, Rio de Janeiro 21941-570, Brazil; (C.A.); (D.M.); (T.F.C.); (A.T.)
| | | | - Erika Martins de Carvalho
- Unidades de Apoio ao Diagnóstico da COVID-19, Rio de Janeiro 21040-900, Brazil; (I.V.d.S.); (E.M.d.C.)
| | - Mario Sergio Ribeiro
- Secretaria Estadual de Saúde do Rio de Janeiro, Rio de Janeiro 20031-142, Brazil; (M.S.R.); (S.C.); (C.M.B.d.M.)
| | - Silvia Carvalho
- Secretaria Estadual de Saúde do Rio de Janeiro, Rio de Janeiro 20031-142, Brazil; (M.S.R.); (S.C.); (C.M.B.d.M.)
| | - Flávio Dias da Silva
- Secretaria Municipal de Saúde Rio de Janeiro, Rio de Janeiro 20211-901, Brazil; (F.D.d.S.); (M.H.d.O.G.); (C.L.P.R.)
| | | | - Leandro Magalhães de Souza
- Laboratório Central de Saúde Pública Noel Nutels, Rio de Janeiro 20231-092, Brazil; (L.M.d.S.); (C.G.d.S.); (A.C.C.)
| | - Cristiane Gomes da Silva
- Laboratório Central de Saúde Pública Noel Nutels, Rio de Janeiro 20231-092, Brazil; (L.M.d.S.); (C.G.d.S.); (A.C.C.)
| | - Caio Luiz Pereira Ribeiro
- Secretaria Municipal de Saúde Rio de Janeiro, Rio de Janeiro 20211-901, Brazil; (F.D.d.S.); (M.H.d.O.G.); (C.L.P.R.)
| | - Andréa Cony Cavalcanti
- Laboratório Central de Saúde Pública Noel Nutels, Rio de Janeiro 20231-092, Brazil; (L.M.d.S.); (C.G.d.S.); (A.C.C.)
| | - Claudia Maria Braga de Mello
- Secretaria Estadual de Saúde do Rio de Janeiro, Rio de Janeiro 20031-142, Brazil; (M.S.R.); (S.C.); (C.M.B.d.M.)
| | | | - Amilcar Tanuri
- Departamento de Genética, Instituto de Biologia, Universidade Federal do Rio de Janeiro, Rio de Janeiro 21941-570, Brazil; (C.A.); (D.M.); (T.F.C.); (A.T.)
| | - Ana Tereza R Vasconcelos
- Laboratório de Bioinformática, Laboratório Nacional de Computação Científica, Petrópolis 25651-076, Brazil; (R.d.S.F.J.); (A.P.L.); (L.G.P.d.A.); (L.C.); (D.T.M.); (Y.M.); (O.B.); (A.L.G.); (A.P.d.C.G.); (R.B.G.)
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Borda V, da Silva Francisco Junior R, Carvalho JB, Morais GL, Duque Rossi Á, Pezzuto P, Azevedo GS, Schamber-Reis BL, Portari EA, Melo A, Moreira MEL, Guida LC, Cunha DP, Gomes L, Vasconcelos ZFM, Faucz FR, Tanuri A, Stratakis CA, Aguiar RS, Cardoso CC, de Vasconcelos ATR. Whole-exome sequencing reveals insights into genetic susceptibility to Congenital Zika Syndrome. PLoS Negl Trop Dis 2021; 15:e0009507. [PMID: 34125832 PMCID: PMC8224898 DOI: 10.1371/journal.pntd.0009507] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2020] [Revised: 06/24/2021] [Accepted: 05/26/2021] [Indexed: 12/30/2022] Open
Abstract
Congenital Zika Syndrome (CZS) is a critical illness with a wide range of severity caused by Zika virus (ZIKV) infection during pregnancy. Life-threatening neurodevelopmental dysfunctions are among the most common phenotypes observed in affected newborns. Risk factors that contribute to susceptibility and response to ZIKV infection may be related to the virus itself, the environment, and maternal genetic background. Nevertheless, the newborn’s genetic contribution to the critical illness is still not elucidated. Here, we aimed to identify possible genetic variants as well as relevant biological pathways that might be associated with CZS phenotypes. For this purpose, we performed a whole-exome sequencing in 40 children born to women with confirmed exposure to ZIKV during pregnancy. We investigated the occurrence of rare harmful single-nucleotide variants (SNVs) possibly associated with inborn errors in genes ontologically related to CZS phenotypes. Moreover, an exome-wide association analysis was also performed using a case-control design (29 CZS cases and 11 controls), for both common and rare variants. Five out of the 29 CZS patients harbored known pathogenic variants likely to contribute to mild to severe manifestations observed. Approximately, 30% of affected individuals carried at least one pathogenic or likely pathogenic SNV in genes candidates to play a role in CZS. Our common variant association analysis detected a suggestive protective effect of the rs2076469 in DISP3 gene (p-value: 1.39 x 10−5). The IL12RB2 gene (p-value: 2.18x10-11) also showed an unusual distribution of nonsynonymous rare SNVs in control samples. Finally, genes harboring harmful variants are involved in processes related to CZS phenotypes such as neurological development and immunity. Therefore, both rare and common variations may be likely to contribute as the underlying genetic cause of CZS susceptibility. The variations and pathways identified in this study may also have implications for the development of therapeutic strategies in the future. Since the beginning of Zika virus outbreak in Brazil, five years ago, we still don’t understand the genetic factors associated with the small number of babies born with Congenital Zika Syndrome (CZS). Here, we focused on the host genetic susceptibility by studying the whole-exome of the CZS affected (n = 29) and healthy (n = 11) neonates, both born to ZIKV infected women from Brazil. We applied two strategies: 1) Determine whether cases individuals have pathogenic or harmful variants that explain the CZS outcomes (i.e. microcephaly) independently of ZIKV infection or not, 2) Exploring the common and rare variants association with CZS. We found that common and rare variants in genes like DISP3 and IL12RB2 could explain some level of the susceptibility to CZS. Moreover, by considering these and other candidate genes, we observed an over-representation of Gene Ontology terms related to neurological system, metabolism and microtubule-cytoskeleton organization.
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Affiliation(s)
- Victor Borda
- Laboratório de Bioinformática, Laboratório Nacional de Computação Científica LNCC/MCTIC Petrópolis, Brazil
| | | | - Joseane B. Carvalho
- Laboratório de Bioinformática, Laboratório Nacional de Computação Científica LNCC/MCTIC Petrópolis, Brazil
| | - Guilherme L. Morais
- Laboratório de Bioinformática, Laboratório Nacional de Computação Científica LNCC/MCTIC Petrópolis, Brazil
| | - Átila Duque Rossi
- Laboratório de Virologia Molecular, Instituto de Biologia, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | - Paula Pezzuto
- Laboratório de Virologia Molecular, Instituto de Biologia, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | | | - Bruno L. Schamber-Reis
- Faculdade de Ciências Médicas de Campina Grande, Núcleo de Genética Médica, Centro Universitário UniFacisa, Campina Grande, Brazil
| | | | - Adriana Melo
- Instituto de Pesquisa Professor Amorim Neto, Campina Grande Brazil
- Faculdade de Ciências Médicas de Campina Grande, Núcleo de Genética Médica, Centro Universitário UniFacisa, Campina Grande, Brazil
| | | | | | | | - Leonardo Gomes
- Instituto Fernandes Figueira, Fiocruz, Rio de Janeiro, Brazil
| | | | - Fabio R. Faucz
- Section on Endocrinology and Genetics, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Amilcar Tanuri
- Laboratório de Virologia Molecular, Instituto de Biologia, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | - Constantine A. Stratakis
- Section on Endocrinology and Genetics, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Renato S. Aguiar
- Departamento de Genética, Ecologia e Evolução Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
- * E-mail: (RSA); (CCC); (ATRV)
| | - Cynthia Chester Cardoso
- Laboratório de Virologia Molecular, Instituto de Biologia, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
- * E-mail: (RSA); (CCC); (ATRV)
| | - Ana Tereza Ribeiro de Vasconcelos
- Laboratório de Bioinformática, Laboratório Nacional de Computação Científica LNCC/MCTIC Petrópolis, Brazil
- * E-mail: (RSA); (CCC); (ATRV)
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8
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García-Díaz G, Montalvo-Varela E, Cano-Pérez E, da Silva Francisco Junior R, Rodriguez-Morales A. Usefulness and limitations of implementing rapid tests for the diagnosis of COVID-19 in Latin America. Infez Med 2020; 28:642-644. [PMID: 33257642] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Not available.
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Affiliation(s)
| | | | - Eder Cano-Pérez
- Grupo de Investigación UNIMOL, Universidad de Cartagena, Cartagena de Indias, Colombia; Maestría en Genética, Universidad Simón Bolívar, Barranquilla, Colombia
| | - Ronaldo da Silva Francisco Junior
- Laboratório de Bioinformática, Laboratório Nacional de Computação Científica, Rio de Janeiro, Brazil; Departamento de Genética, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | - AlfonsoJ Rodriguez-Morales
- Public Health and Infection Research Group, Faculty of Health Sciences, Universidad Tecnologica de Pereira, Pereira, Risaralda, Colombia: Grupo de Investigación Biomedicina, Faculty of Medicine, Fundación Universitaria Autónoma de las Américas, Pereira, Risaralda, Colombia; Universidad Privada Franz Tamayo [UNIFRANZ], Cochabamba, Bolivia
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9
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da Silva Francisco Junior R, Dos Santos Ferreira C, Santos E Silva JC, Terra Machado D, Côrtes Martins Y, Ramos V, Simões Carnivali G, Garcia AB, Medina-Acosta E. Pervasive Inter-Individual Variation in Allele-Specific Expression in Monozygotic Twins. Front Genet 2019; 10:1178. [PMID: 31850058 PMCID: PMC6887657 DOI: 10.3389/fgene.2019.01178] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2019] [Accepted: 10/24/2019] [Indexed: 01/19/2023] Open
Abstract
Despite being developed from one zygote, heterokaryotypic monozygotic (MZ) co-twins exhibit discordant karyotypes. Epigenomic studies in biological samples from heterokaryotypic MZ co-twins are of the most significant value for assessing the effects on gene- and allele-specific expression of an extranumerary chromosomal copy or structural chromosomal disparities in otherwise nearly identical germline genetic contributions. Here, we use RNA-Seq data from existing repositories to establish within-pair correlations for the breadth and magnitude of allele-specific expression (ASE) in heterokaryotypic MZ co-twins discordant for trisomy 21 and maternal 21q inheritance, as well as homokaryotypic co-twins. We show that there is a genome-wide disparity at ASE sites between the heterokaryotypic MZ co-twins. Although most of the disparity corresponds to changes in the magnitude of biallelic imbalance, ASE sites switching from either strictly monoallelic to biallelic imbalance or the reverse occur in few genes that are known or predicted to be imprinted, subject to X-chromosome inactivation or A-to-I(G) RNA edited. We also uncovered comparable ASE differences between homokaryotypic MZ twins. The extent of ASE discordance in MZ twins (2.7%) was about 10-fold lower than the expected between pairs of unrelated, non-twin males or females. The results indicate that the observed within-pair dissimilarities in breadth and magnitude of ASE sites in the heterokaryotypic MZ co-twins could not solely be attributable to the aneuploidy and the missing allelic heritability at 21q.
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Affiliation(s)
| | - Cristina Dos Santos Ferreira
- Laboratório de Biotecnologia, Núcleo de Diagnóstico e Investigação Molecular, Universidade Estadual do Norte Fluminense, Campos dos Goytacazes, Brazil
| | - Juan Carlo Santos E Silva
- Laboratório de Biotecnologia, Núcleo de Diagnóstico e Investigação Molecular, Universidade Estadual do Norte Fluminense, Campos dos Goytacazes, Brazil
| | - Douglas Terra Machado
- Laboratório de Biotecnologia, Núcleo de Diagnóstico e Investigação Molecular, Universidade Estadual do Norte Fluminense, Campos dos Goytacazes, Brazil
| | - Yasmmin Côrtes Martins
- Laboratório de Bioinformática, Laboratório Nacional de Computação Científica, Petrópolis, Brazil
| | - Victor Ramos
- Department of Genetics, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, Brazil
| | - Gustavo Simões Carnivali
- Department of Computational Science, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Ana Beatriz Garcia
- Laboratório de Biotecnologia, Núcleo de Diagnóstico e Investigação Molecular, Universidade Estadual do Norte Fluminense, Campos dos Goytacazes, Brazil
| | - Enrique Medina-Acosta
- Laboratório de Biotecnologia, Núcleo de Diagnóstico e Investigação Molecular, Universidade Estadual do Norte Fluminense, Campos dos Goytacazes, Brazil
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10
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de Sá Machado Araújo G, da Silva Francisco Junior R, Dos Santos Ferreira C, Mozer Rodrigues PT, Terra Machado D, Louvain de Souza T, Teixeira de Souza J, Figueiredo Osorio da Silva C, Alves da Silva AF, Andrade CCF, da Silva AT, Ramos V, Garcia AB, Machado FB, Medina-Acosta E. Maternal 5 mCpG Imprints at the PARD6G-AS1 and GCSAML Differentially Methylated Regions Are Decoupled From Parent-of-Origin Expression Effects in Multiple Human Tissues. Front Genet 2018; 9:36. [PMID: 29545821 PMCID: PMC5838017 DOI: 10.3389/fgene.2018.00036] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2017] [Accepted: 01/29/2018] [Indexed: 11/13/2022] Open
Abstract
A hallmark of imprinted genes in mammals is the occurrence of parent-of-origin-dependent asymmetry of DNA cytosine methylation (5mC) of alleles at CpG islands (CGIs) in their promoter regions. This 5mCpG asymmetry between the parental alleles creates allele-specific imprinted differentially methylated regions (iDMRs). iDMRs are often coupled to the transcriptional repression of the methylated allele and the activation of the unmethylated allele in a tissue-specific, developmental-stage-specific and/or isoform-specific fashion. iDMRs function as regulatory platforms, built through the recruitment of chemical modifications to histones to achieve differential, parent-of-origin-dependent chromatin segmentation states. Here, we used a comparative computational data mining approach to identify 125 novel constitutive candidate iDMRs that integrate the maximal number of allele-specific methylation region records overlapping CGIs in human methylomes. Twenty-nine candidate iDMRs display gametic 5mCpG asymmetry, and another 96 are candidate secondary iDMRs. We established the maternal origin of the 5mCpG imprints of one gametic (PARD6G-AS1) and one secondary (GCSAML) iDMRs. We also found a constitutively hemimethylated, nonimprinted domain at the PWWP2AP1 promoter CGI with oocyte-derived methylation asymmetry. Given that the 5mCpG level at the iDMRs is not a sufficient criterion to predict active or silent locus states and that iDMRs can regulate genes from a distance of more than 1 Mb, we used RNA-Seq experiments from the Genotype-Tissue Expression project and public archives to assess the transcriptional expression profiles of SNPs across 4.6 Mb spans around the novel maternal iDMRs. We showed that PARD6G-AS1 and GCSAML are expressed biallelically in multiple tissues. We found evidence of tissue-specific monoallelic expression of ZNF124 and OR2L13, located 363 kb upstream and 419 kb downstream, respectively, of the GCSAML iDMR. We hypothesize that the GCSAML iDMR regulates the tissue-specific, monoallelic expression of ZNF124 but not of OR2L13. We annotated the non-coding epigenomic marks in the two maternal iDMRs using data from the Roadmap Epigenomics project and showed that the PARD6G-AS1 and GCSAML iDMRs achieve contrasting activation and repression chromatin segmentations. Lastly, we found that the maternal 5mCpG imprints are perturbed in several hematopoietic cancers. We conclude that the maternal 5mCpG imprints at PARD6G-AS1 and GCSAML iDMRs are decoupled from parent-of-origin transcriptional expression effects in multiple tissues.
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Affiliation(s)
- Graziela de Sá Machado Araújo
- Núcleo de Diagnóstico e Investigação Molecular, Laboratório de Biotecnologia, Centro de Biociências e Biotecnologia, Universidade Estadual do Norte Fluminense Darcy Ribeiro, Campos dos Goytacazes, Brazil
| | - Ronaldo da Silva Francisco Junior
- Núcleo de Diagnóstico e Investigação Molecular, Laboratório de Biotecnologia, Centro de Biociências e Biotecnologia, Universidade Estadual do Norte Fluminense Darcy Ribeiro, Campos dos Goytacazes, Brazil.,Laboratório Nacional de Computação Científica, Petrópolis, Brazil
| | - Cristina Dos Santos Ferreira
- Núcleo de Diagnóstico e Investigação Molecular, Laboratório de Biotecnologia, Centro de Biociências e Biotecnologia, Universidade Estadual do Norte Fluminense Darcy Ribeiro, Campos dos Goytacazes, Brazil
| | - Pedro Thyago Mozer Rodrigues
- Núcleo de Diagnóstico e Investigação Molecular, Laboratório de Biotecnologia, Centro de Biociências e Biotecnologia, Universidade Estadual do Norte Fluminense Darcy Ribeiro, Campos dos Goytacazes, Brazil
| | - Douglas Terra Machado
- Núcleo de Diagnóstico e Investigação Molecular, Laboratório de Biotecnologia, Centro de Biociências e Biotecnologia, Universidade Estadual do Norte Fluminense Darcy Ribeiro, Campos dos Goytacazes, Brazil
| | - Thais Louvain de Souza
- Núcleo de Diagnóstico e Investigação Molecular, Laboratório de Biotecnologia, Centro de Biociências e Biotecnologia, Universidade Estadual do Norte Fluminense Darcy Ribeiro, Campos dos Goytacazes, Brazil.,Faculdade de Medicina de Campos, Campos dos Goytacazes, Brazil
| | - Jozimara Teixeira de Souza
- Núcleo de Diagnóstico e Investigação Molecular, Laboratório de Biotecnologia, Centro de Biociências e Biotecnologia, Universidade Estadual do Norte Fluminense Darcy Ribeiro, Campos dos Goytacazes, Brazil
| | - Cleiton Figueiredo Osorio da Silva
- Núcleo de Diagnóstico e Investigação Molecular, Laboratório de Biotecnologia, Centro de Biociências e Biotecnologia, Universidade Estadual do Norte Fluminense Darcy Ribeiro, Campos dos Goytacazes, Brazil
| | - Antônio Francisco Alves da Silva
- Núcleo de Diagnóstico e Investigação Molecular, Laboratório de Biotecnologia, Centro de Biociências e Biotecnologia, Universidade Estadual do Norte Fluminense Darcy Ribeiro, Campos dos Goytacazes, Brazil
| | - Claudia Caixeta Franco Andrade
- Núcleo de Diagnóstico e Investigação Molecular, Laboratório de Biotecnologia, Centro de Biociências e Biotecnologia, Universidade Estadual do Norte Fluminense Darcy Ribeiro, Campos dos Goytacazes, Brazil.,Faculdade Metropolitana São Carlos, Bom Jesus do Itabapoana, Brazil
| | - Alan Tardin da Silva
- Núcleo de Diagnóstico e Investigação Molecular, Laboratório de Biotecnologia, Centro de Biociências e Biotecnologia, Universidade Estadual do Norte Fluminense Darcy Ribeiro, Campos dos Goytacazes, Brazil
| | - Victor Ramos
- Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, Brazil
| | - Ana Beatriz Garcia
- Núcleo de Diagnóstico e Investigação Molecular, Laboratório de Biotecnologia, Centro de Biociências e Biotecnologia, Universidade Estadual do Norte Fluminense Darcy Ribeiro, Campos dos Goytacazes, Brazil
| | - Filipe Brum Machado
- Núcleo de Diagnóstico e Investigação Molecular, Laboratório de Biotecnologia, Centro de Biociências e Biotecnologia, Universidade Estadual do Norte Fluminense Darcy Ribeiro, Campos dos Goytacazes, Brazil
| | - Enrique Medina-Acosta
- Núcleo de Diagnóstico e Investigação Molecular, Laboratório de Biotecnologia, Centro de Biociências e Biotecnologia, Universidade Estadual do Norte Fluminense Darcy Ribeiro, Campos dos Goytacazes, Brazil
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11
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Alves da Silva AF, Machado FB, Pavarino ÉC, Biselli-Périco JM, Zampieri BL, da Silva Francisco Junior R, Mozer Rodrigues PT, Terra Machado D, Santos-Rebouças CB, Gomes Fernandes M, Chuva de Sousa Lopes SM, Lopes Rios ÁF, Medina-Acosta E. Trisomy 21 Alters DNA Methylation in Parent-of-Origin-Dependent and -Independent Manners. PLoS One 2016; 11:e0154108. [PMID: 27100087 PMCID: PMC4839675 DOI: 10.1371/journal.pone.0154108] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2015] [Accepted: 04/09/2016] [Indexed: 12/31/2022] Open
Abstract
The supernumerary chromosome 21 in Down syndrome differentially affects the methylation statuses at CpG dinucleotide sites and creates genome-wide transcriptional dysregulation of parental alleles, ultimately causing diverse pathologies. At present, it is unknown whether those effects are dependent or independent of the parental origin of the nondisjoined chromosome 21. Linkage analysis is a standard method for the determination of the parental origin of this aneuploidy, although it is inadequate in cases with deficiency of samples from the progenitors. Here, we assessed the reliability of the epigenetic 5mCpG imprints resulting in the maternally (oocyte)-derived allele methylation at a differentially methylated region (DMR) of the candidate imprinted WRB gene for asserting the parental origin of chromosome 21. We developed a methylation-sensitive restriction enzyme-specific PCR assay, based on the WRB DMR, across single nucleotide polymorphisms (SNPs) to examine the methylation statuses in the parental alleles. In genomic DNA from blood cells of either disomic or trisomic subjects, the maternal alleles were consistently methylated, while the paternal alleles were unmethylated. However, the supernumerary chromosome 21 did alter the methylation patterns at the RUNX1 (chromosome 21) and TMEM131 (chromosome 2) CpG sites in a parent-of-origin-independent manner. To evaluate the 5mCpG imprints, we conducted a computational comparative epigenomic analysis of transcriptome RNA sequencing (RNA-Seq) and histone modification expression patterns. We found allele fractions consistent with the transcriptional biallelic expression of WRB and ten neighboring genes, despite the similarities in the confluence of both a 17-histone modification activation backbone module and a 5-histone modification repressive module between the WRB DMR and the DMRs of six imprinted genes. We concluded that the maternally inherited 5mCpG imprints at the WRB DMR are uncoupled from the parental allele expression of WRB and ten neighboring genes in several tissues and that trisomy 21 alters DNA methylation in parent-of-origin-dependent and -independent manners.
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Affiliation(s)
- Antônio Francisco Alves da Silva
- Laboratory of Biotechnology, Universidade Estadual do Norte Fluminense Darcy Ribeiro, Campos do Goytacazes, Rio de Janeiro, Brazil
- Molecular Identification and Diagnostics Unit, Hospital Escola Álvaro Alvim, Campos dos Goytacazes, Rio de Janeiro, Brazil
- Graduate Program in Biosciences and Biotechnology, Center for Biosciences and Biotechnology, Universidade Estadual do Norte Fluminense Darcy Ribeiro, Rio de Janeiro, Brazil
- * E-mail: (AFAS); (FBM); (EM-A)
| | - Filipe Brum Machado
- Laboratory of Biotechnology, Universidade Estadual do Norte Fluminense Darcy Ribeiro, Campos do Goytacazes, Rio de Janeiro, Brazil
- Molecular Identification and Diagnostics Unit, Hospital Escola Álvaro Alvim, Campos dos Goytacazes, Rio de Janeiro, Brazil
- Postgraduate Program in Biosciences and Biotechnology, Center for Biosciences and Biotechnology, Universidade Estadual do Norte Fluminense Darcy Ribeiro, Rio de Janeiro, Brazil
- * E-mail: (AFAS); (FBM); (EM-A)
| | | | | | | | - Ronaldo da Silva Francisco Junior
- Laboratory of Biotechnology, Universidade Estadual do Norte Fluminense Darcy Ribeiro, Campos do Goytacazes, Rio de Janeiro, Brazil
- Molecular Identification and Diagnostics Unit, Hospital Escola Álvaro Alvim, Campos dos Goytacazes, Rio de Janeiro, Brazil
| | - Pedro Thyago Mozer Rodrigues
- Laboratory of Biotechnology, Universidade Estadual do Norte Fluminense Darcy Ribeiro, Campos do Goytacazes, Rio de Janeiro, Brazil
- Molecular Identification and Diagnostics Unit, Hospital Escola Álvaro Alvim, Campos dos Goytacazes, Rio de Janeiro, Brazil
| | - Douglas Terra Machado
- Laboratory of Biotechnology, Universidade Estadual do Norte Fluminense Darcy Ribeiro, Campos do Goytacazes, Rio de Janeiro, Brazil
- Molecular Identification and Diagnostics Unit, Hospital Escola Álvaro Alvim, Campos dos Goytacazes, Rio de Janeiro, Brazil
| | | | - Maria Gomes Fernandes
- Department of Anatomy and Embryology, Leiden University Medical Center, Leiden, South Holland, The Netherlands
| | | | - Álvaro Fabricio Lopes Rios
- Laboratory of Biotechnology, Universidade Estadual do Norte Fluminense Darcy Ribeiro, Campos do Goytacazes, Rio de Janeiro, Brazil
| | - Enrique Medina-Acosta
- Laboratory of Biotechnology, Universidade Estadual do Norte Fluminense Darcy Ribeiro, Campos do Goytacazes, Rio de Janeiro, Brazil
- Molecular Identification and Diagnostics Unit, Hospital Escola Álvaro Alvim, Campos dos Goytacazes, Rio de Janeiro, Brazil
- Graduate Program in Biosciences and Biotechnology, Center for Biosciences and Biotechnology, Universidade Estadual do Norte Fluminense Darcy Ribeiro, Rio de Janeiro, Brazil
- * E-mail: (AFAS); (FBM); (EM-A)
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