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1.
BMC Bioinformatics ; 21(Suppl 14): 368, 2020 Sep 30.
Artigo em Inglês | MEDLINE | ID: mdl-32998690

RESUMO

BACKGROUND: Lung cancer is the leading cause of the largest number of deaths worldwide and lung adenocarcinoma is the most common form of lung cancer. In order to understand the molecular basis of lung adenocarcinoma, integrative analysis have been performed by using genomics, transcriptomics, epigenomics, proteomics and clinical data. Besides, molecular prognostic signatures have been generated for lung adenocarcinoma by using gene expression levels in tumor samples. However, we need signatures including different types of molecular data, even cohort or patient-based biomarkers which are the candidates of molecular targeting. RESULTS: We built an R pipeline to carry out an integrated meta-analysis of the genomic alterations including single-nucleotide variations and the copy number variations, transcriptomics variations through RNA-seq and clinical data of patients with lung adenocarcinoma in The Cancer Genome Atlas project. We integrated significant genes including single-nucleotide variations or the copy number variations, differentially expressed genes and those in active subnetworks to construct a prognosis signature. Cox proportional hazards model with Lasso penalty and LOOCV was used to identify best gene signature among different gene categories. We determined a 12-gene signature (BCHE, CCNA1, CYP24A1, DEPTOR, MASP2, MGLL, MYO1A, PODXL2, RAPGEF3, SGK2, TNNI2, ZBTB16) for prognostic risk prediction based on overall survival time of the patients with lung adenocarcinoma. The patients in both training and test data were clustered into high-risk and low-risk groups by using risk scores of the patients calculated based on selected gene signature. The overall survival probability of these risk groups was highly significantly different for both training and test datasets. CONCLUSIONS: This 12-gene signature could predict the prognostic risk of the patients with lung adenocarcinoma in TCGA and they are potential predictors for the survival-based risk clustering of the patients with lung adenocarcinoma. These genes can be used to cluster patients based on molecular nature and the best candidates of drugs for the patient clusters can be proposed. These genes also have a high potential for targeted cancer therapy of patients with lung adenocarcinoma.


Assuntos
Adenocarcinoma de Pulmão/patologia , Genômica/métodos , Neoplasias Pulmonares/patologia , Transcriptoma , Adenocarcinoma de Pulmão/genética , Adenocarcinoma de Pulmão/mortalidade , Área Sob a Curva , Análise por Conglomerados , Variações do Número de Cópias de DNA , Bases de Dados Genéticas , Regulação Neoplásica da Expressão Gênica , Humanos , Neoplasias Pulmonares/genética , Neoplasias Pulmonares/mortalidade , Estadiamento de Neoplasias , Prognóstico , Modelos de Riscos Proporcionais , Mapas de Interação de Proteínas/genética , Curva ROC , Fatores de Risco , Taxa de Sobrevida
2.
PLoS One ; 15(8): e0230404, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32866150

RESUMO

High-throughput SNP genotyping has become a precondition to move to higher precision and wider genome coverage genetic analysis of natural and breeding populations of non-model species. We developed a 44,318 annotated SNP catalog for Araucaria angustifolia, a grandiose subtropical conifer tree, one of the only two native Brazilian gymnosperms, critically endangered due to its valuable wood and seeds. Following transcriptome assembly and annotation, SNPs were discovered from RNA-seq and pooled RAD-seq data. From the SNP catalog, an Axiom® SNP array with 3,038 validated SNPs was developed and used to provide a comprehensive look at the genetic diversity and structure of 15 populations across the natural range of the species. RNA-seq was a far superior source of SNPs when compared to RAD-seq in terms of conversion rate to polymorphic markers on the array, likely due to the more efficient complexity reduction of the huge conifer genome. By matching microsatellite and SNP data on the same set of A. angustifolia individuals, we show that SNPs reflect more precisely the actual genome-wide patterns of genetic diversity and structure, challenging previous microsatellite-based assessments. Moreover, SNPs corroborated the known major north-south genetic cline, but allowed a more accurate attribution to regional versus among-population differentiation, indicating the potential to select ancestry-informative markers. The availability of a public, user-friendly 3K SNP array for A. angustifolia and a catalog of 44,318 SNPs predicted to provide ~29,000 informative SNPs across ~20,000 loci across the genome, will allow tackling still unsettled questions on its evolutionary history, toward a more comprehensive picture of the origin, past dynamics and future trend of the species' genetic resources. Additionally, but not less importantly, the SNP array described, unlocks the potential to adopt genomic prediction methods to accelerate the still very timid efforts of systematic tree breeding of A. angustifolia.


Assuntos
Araucaria/genética , Brasil , Genoma de Planta/genética , Genômica/métodos , Genótipo , Repetições de Microssatélites/genética , Polimorfismo de Nucleotídeo Único/genética , Traqueófitas/genética , Transcriptoma/genética , Árvores/genética
3.
BMC Bioinformatics ; 21(1): 378, 2020 Sep 03.
Artigo em Inglês | MEDLINE | ID: mdl-32883210

RESUMO

BACKGROUND: The improvements in genomics methods coupled with readily accessible high-throughput sequencing have contributed to our understanding of microbial species, metagenomes, infectious diseases and more. To maximize the impact of these genomics studies, it is important that data from biological samples will become publicly available with standardized metadata. The availability of data at public archives provides the hope that greater insights could be obtained through integration with multi-omics data, reproducibility of published studies, or meta-analyses of large diverse datasets. These datasets should include a description of the host, organism, environmental source of the specimen, spatial-temporal information and other relevant metadata, but unfortunately these attributes are often missing and when present, they show inconsistencies in the use of metadata standards and ontologies. RESULTS: METAGENOTE ( https://metagenote.niaid.nih.gov ) is a web portal that greatly facilitates the annotation of samples from genomic studies and streamlines the submission process of sequencing files and metadata to the Sequence Read Archive (SRA) (Leinonen R, et al, Nucleic Acids Res, 39:D19-21, 2011) for public access. This platform offers a wide selection of packages for different types of biological and experimental studies with a special emphasis on the standardization of metadata reporting. These packages follow the guidelines from the MIxS standards developed by the Genomics Standard Consortium (GSC) and adopted by the three partners of the International Nucleotides Sequencing Database Collaboration (INSDC) (Cochrane G, et al, Nucleic Acids Res, 44:D48-50, 2016) - National Center for Biotechnology Information (NCBI), European Bioinformatics Institute (EBI) and the DNA Data Bank of Japan (DDBJ). METAGENOTE then compiles, validates and manages the submission through an easy-to-use web interface minimizing submission errors and eliminating the need for submitting sequencing files via a separate file transfer mechanism. CONCLUSIONS: METAGENOTE is a public resource that focuses on simplifying the annotation and submission process of data with its corresponding metadata. Users of METAGENOTE will benefit from the easy to use annotation interface but most importantly will be encouraged to publish metadata following standards and ontologies that make the public data available for reuse.


Assuntos
Genômica/métodos , Interface Usuário-Computador , Animais , Bases de Dados Genéticas , Humanos
4.
PLoS Comput Biol ; 16(9): e1008269, 2020 09.
Artigo em Inglês | MEDLINE | ID: mdl-32941419

RESUMO

We propose an efficient framework for genetic subtyping of SARS-CoV-2, the novel coronavirus that causes the COVID-19 pandemic. Efficient viral subtyping enables visualization and modeling of the geographic distribution and temporal dynamics of disease spread. Subtyping thereby advances the development of effective containment strategies and, potentially, therapeutic and vaccine strategies. However, identifying viral subtypes in real-time is challenging: SARS-CoV-2 is a novel virus, and the pandemic is rapidly expanding. Viral subtypes may be difficult to detect due to rapid evolution; founder effects are more significant than selection pressure; and the clustering threshold for subtyping is not standardized. We propose to identify mutational signatures of available SARS-CoV-2 sequences using a population-based approach: an entropy measure followed by frequency analysis. These signatures, Informative Subtype Markers (ISMs), define a compact set of nucleotide sites that characterize the most variable (and thus most informative) positions in the viral genomes sequenced from different individuals. Through ISM compression, we find that certain distant nucleotide variants covary, including non-coding and ORF1ab sites covarying with the D614G spike protein mutation which has become increasingly prevalent as the pandemic has spread. ISMs are also useful for downstream analyses, such as spatiotemporal visualization of viral dynamics. By analyzing sequence data available in the GISAID database, we validate the utility of ISM-based subtyping by comparing spatiotemporal analyses using ISMs to epidemiological studies of viral transmission in Asia, Europe, and the United States. In addition, we show the relationship of ISMs to phylogenetic reconstructions of SARS-CoV-2 evolution, and therefore, ISMs can play an important complementary role to phylogenetic tree-based analysis, such as is done in the Nextstrain project. The developed pipeline dynamically generates ISMs for newly added SARS-CoV-2 sequences and updates the visualization of pandemic spatiotemporal dynamics, and is available on Github at https://github.com/EESI/ISM (Jupyter notebook), https://github.com/EESI/ncov_ism (command line tool) and via an interactive website at https://covid19-ism.coe.drexel.edu/.


Assuntos
Betacoronavirus/classificação , Betacoronavirus/genética , Infecções por Coronavirus , Genômica/métodos , Pandemias , Pneumonia Viral , Infecções por Coronavirus/epidemiologia , Infecções por Coronavirus/transmissão , Infecções por Coronavirus/virologia , Evolução Molecular , Marcadores Genéticos/genética , Genoma Viral/genética , Humanos , Mutação/genética , Filogenia , Pneumonia Viral/epidemiologia , Pneumonia Viral/transmissão , Pneumonia Viral/virologia , RNA Viral/genética , Alinhamento de Sequência , Análise de Sequência de RNA , Análise Espaço-Temporal
5.
Nat Commun ; 11(1): 4376, 2020 09 01.
Artigo em Inglês | MEDLINE | ID: mdl-32873808

RESUMO

Genomic sequencing has significant potential to inform public health management for SARS-CoV-2. Here we report high-throughput genomics for SARS-CoV-2, sequencing 80% of cases in Victoria, Australia (population 6.24 million) between 6 January and 14 April 2020 (total 1,333 COVID-19 cases). We integrate epidemiological, genomic and phylodynamic data to identify clusters and impact of interventions. The global diversity of SARS-CoV-2 is represented, consistent with multiple importations. Seventy-six distinct genomic clusters were identified, including large clusters associated with social venues, healthcare and cruise ships. Sequencing sequential samples from 98 patients reveals minimal intra-patient SARS-CoV-2 genomic diversity. Phylodynamic modelling indicates a significant reduction in the effective viral reproductive number (Re) from 1.63 to 0.48 after implementing travel restrictions and physical distancing. Our data provide a concrete framework for the use of SARS-CoV-2 genomics in public health responses, including its use to rapidly identify SARS-CoV-2 transmission chains, increasingly important as social restrictions ease globally.


Assuntos
Betacoronavirus/genética , Infecções por Coronavirus/epidemiologia , Infecções por Coronavirus/virologia , Pneumonia Viral/epidemiologia , Pneumonia Viral/virologia , Adulto , Austrália/epidemiologia , Betacoronavirus/isolamento & purificação , Infecções por Coronavirus/transmissão , Feminino , Genoma Viral , Genômica/métodos , Pessoal de Saúde , Humanos , Masculino , Pessoa de Meia-Idade , Epidemiologia Molecular , Pandemias , Filogenia , Pneumonia Viral/transmissão , Saúde Pública , Estudos Retrospectivos , Viagem
6.
Nat Commun ; 11(1): 4374, 2020 09 01.
Artigo em Inglês | MEDLINE | ID: mdl-32873787

RESUMO

Oncogene amplification, a major driver of cancer pathogenicity, is often mediated through focal amplification of genomic segments. Recent results implicate extrachromosomal DNA (ecDNA) as the primary driver of focal copy number amplification (fCNA) - enabling gene amplification, rapid tumor evolution, and the rewiring of regulatory circuitry. Resolving an fCNA's structure is a first step in deciphering the mechanisms of its genesis and the fCNA's subsequent biological consequences. We introduce a computational method, AmpliconReconstructor (AR), for integrating optical mapping (OM) of long DNA fragments (>150 kb) with next-generation sequencing (NGS) to resolve fCNAs at single-nucleotide resolution. AR uses an NGS-derived breakpoint graph alongside OM scaffolds to produce high-fidelity reconstructions. After validating its performance through multiple simulation strategies, AR reconstructed fCNAs in seven cancer cell lines to reveal the complex architecture of ecDNA, a breakage-fusion-bridge and other complex rearrangements. By reconstructing the rearrangement signatures associated with an fCNA's generative mechanism, AR enables a more thorough understanding of the origins of fCNAs.


Assuntos
Amplificação de Genes , Genômica/métodos , Neoplasias/genética , Oncogenes/genética , Linhagem Celular Tumoral , Mapeamento Cromossômico/métodos , Análise Citogenética , Genoma Humano/genética , Sequenciamento de Nucleotídeos em Larga Escala/métodos , Humanos
7.
PLoS Comput Biol ; 16(9): e1008182, 2020 09.
Artigo em Inglês | MEDLINE | ID: mdl-32931516

RESUMO

Recent advances in experimental biology allow creation of datasets where several genome-wide data types (called omics) are measured per sample. Integrative analysis of multi-omic datasets in general, and clustering of samples in such datasets specifically, can improve our understanding of biological processes and discover different disease subtypes. In this work we present MONET (Multi Omic clustering by Non-Exhaustive Types), which presents a unique approach to multi-omic clustering. MONET discovers modules of similar samples, such that each module is allowed to have a clustering structure for only a subset of the omics. This approach differs from most existent multi-omic clustering algorithms, which assume a common structure across all omics, and from several recent algorithms that model distinct cluster structures. We tested MONET extensively on simulated data, on an image dataset, and on ten multi-omic cancer datasets from TCGA. Our analysis shows that MONET compares favorably with other multi-omic clustering methods. We demonstrate MONET's biological and clinical relevance by analyzing its results for Ovarian Serous Cystadenocarcinoma. We also show that MONET is robust to missing data, can cluster genes in multi-omic dataset, and reveal modules of cell types in single-cell multi-omic data. Our work shows that MONET is a valuable tool that can provide complementary results to those provided by existent algorithms for multi-omic analysis.


Assuntos
Algoritmos , Genômica/métodos , Análise por Conglomerados , Bases de Dados Genéticas , Humanos , Neoplasias/genética , Neoplasias/metabolismo , Análise de Célula Única
8.
PLoS Comput Biol ; 16(9): e1008194, 2020 09.
Artigo em Inglês | MEDLINE | ID: mdl-32936799

RESUMO

CRISPR screens are a powerful technology for the identification of genome sequences that affect cellular phenotypes such as gene expression, survival, and proliferation. By targeting non-coding sequences for perturbation, CRISPR screens have the potential to systematically discover novel functional sequences, however, a lack of purpose-built analysis tools limits the effectiveness of this approach. Here we describe RELICS, a Bayesian hierarchical model for the discovery of functional sequences from CRISPR screens. RELICS specifically addresses many of the challenges of non-coding CRISPR screens such as the unknown locations of functional sequences, overdispersion in the observed single guide RNA counts, and the need to combine information across multiple pools in an experiment. RELICS outperforms existing methods with higher precision, higher recall, and finer-resolution predictions on simulated datasets. We apply RELICS to published CRISPR interference and CRISPR activation screens to predict and experimentally validate novel regulatory sequences that are missed by other analysis methods. In summary, RELICS is a powerful new analysis method for CRISPR screens that enables the discovery of functional sequences with unprecedented resolution and accuracy.


Assuntos
Sistemas CRISPR-Cas/genética , Genômica/métodos , Análise de Sequência de DNA/métodos , Software , Teorema de Bayes , Humanos , Células Jurkat , RNA Guia/genética
9.
Nat Commun ; 11(1): 4225, 2020 08 24.
Artigo em Inglês | MEDLINE | ID: mdl-32839463

RESUMO

Gallbladder cancer (GBC) is an aggressive gastrointestinal malignancy with no approved targeted therapy. Here, we analyze exomes (n = 160), transcriptomes (n = 115), and low pass whole genomes (n = 146) from 167 gallbladder cancers (GBCs) from patients in Korea, India and Chile. In addition, we also sequence samples from 39 GBC high-risk patients and detect evidence of early cancer-related genomic lesions. Among the several significantly mutated genes not previously linked to GBC are ETS domain genes ELF3 and EHF, CTNNB1, APC, NSD1, KAT8, STK11 and NFE2L2. A majority of ELF3 alterations are frame-shift mutations that result in several cancer-specific neoantigens that activate T-cells indicating that they are cancer vaccine candidates. In addition, we identify recurrent alterations in KEAP1/NFE2L2 and WNT pathway in GBC. Taken together, these define multiple targetable therapeutic interventions opportunities for GBC treatment and management.


Assuntos
Proteínas de Ligação a DNA/genética , Mutação da Fase de Leitura , Neoplasias da Vesícula Biliar/genética , Predisposição Genética para Doença/genética , Proteínas Proto-Oncogênicas c-ets/genética , Fatores de Transcrição/genética , Vacinas Anticâncer/genética , Vacinas Anticâncer/imunologia , Chile , Proteínas de Ligação a DNA/imunologia , Proteínas de Ligação a DNA/metabolismo , Neoplasias da Vesícula Biliar/diagnóstico , Neoplasias da Vesícula Biliar/metabolismo , Perfilação da Expressão Gênica/métodos , Regulação Neoplásica da Expressão Gênica , Genômica/métodos , Humanos , Índia , Proteína 1 Associada a ECH Semelhante a Kelch/genética , Proteína 1 Associada a ECH Semelhante a Kelch/metabolismo , Fator 2 Relacionado a NF-E2/genética , Fator 2 Relacionado a NF-E2/metabolismo , Proteínas Proto-Oncogênicas c-ets/imunologia , Proteínas Proto-Oncogênicas c-ets/metabolismo , República da Coreia , Fatores de Transcrição/imunologia , Fatores de Transcrição/metabolismo , Via de Sinalização Wnt/genética , beta Catenina/genética , beta Catenina/metabolismo
10.
PLoS Comput Biol ; 16(8): e1007261, 2020 08.
Artigo em Inglês | MEDLINE | ID: mdl-32810130

RESUMO

We describe JBrowse Connect, an optional expansion to the JBrowse genome browser, targeted at developers. JBrowse Connect allows live messaging, notifications for new annotation tracks, heavy-duty analyses initiated by the user from within the browser, and other dynamic features. We present example applications of JBrowse Connect that allow users 1) to specify and execute BLAST searches by either running on the same host as the webserver, with a self-contained BLAST module leveraging NCBI Blast+ commands, or via a managed Galaxy instance that can optionally run on a different host, and 2) to run the primer design service Primer3. JBrowse Connect allows users to track job progress and view results in the context of the browser. The software is available under a choice of open source licenses including LGPL and the Artistic License.


Assuntos
Bases de Dados Genéticas , Genômica/métodos , Software , Internet
11.
Gene ; 762: 145040, 2020 Dec 15.
Artigo em Inglês | MEDLINE | ID: mdl-32777520

RESUMO

Circular RNAs (circRNA) are a special kind of covalently closed single-stranded RNA molecules. They have been shown to control and coordinate various biological processes. Recent researches show that circRNAs are closely associated with numerous chronic human diseases. Identification of circRNA-disease associations will contribute towards diagnosing the pathogenesis of diseases. Experimental methods for finding the relation between the diseases and their causal circRNAs are difficult and time-consuming. So computational methods are of critical need for predicting the associations between circRNAs and various human diseases. In this study, we propose an ensemble approach AE-DNN, which relies on autoencoder and deep neural networks to predict new circRNA-disease relationships. We utilized circRNA sequence similarity, disease semantic similarity, and Gaussian interaction profile kernel similarities of circRNAs and diseases for feature construction. The constructed features are fed to a deep autoencoder, and the extracted compact, high-level features are fed to the deep neural network for association prediction. We conducted 5-fold and 10-fold cross-validation experiments to assess the performance; AE-DNN could achieve AUC scores of 0.9392 and 0.9431, respectively. Experimental results and case studies indicate the robustness of our model in circRNA-disease association prediction.


Assuntos
Aprendizado Profundo , Predisposição Genética para Doença , RNA Circular/genética , Estudo de Associação Genômica Ampla/métodos , Genômica/métodos , Humanos , RNA Circular/metabolismo
12.
Methods Mol Biol ; 2203: 167-184, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32833212

RESUMO

The Escherichia coli and vaccinia virus-based reverse genetics systems have been widely applied for the manipulation and engineering of coronavirus genomes. These systems, however, present several limitations and are sometimes difficult to establish in a timely manner for (re-)emerging viruses. In this chapter, we present a new universal reverse genetics platform for the assembly and engineering of infectious full-length cDNAs using yeast-based transformation-associated recombination cloning. This novel assembly method not only results in stable coronavirus infectious full-length cDNAs cloned in the yeast Saccharomyces cerevisiae but also fosters and accelerates the manipulation of their genomes. Such a platform is widely applicable for the scientific community, as it requires no specific equipment and can be performed in a standard laboratory setting. The protocol described can be easily adapted to virtually all known or emerging coronaviruses, such as Middle East respiratory syndrome coronavirus (MERS-CoV).


Assuntos
Coronavirus/genética , DNA Complementar/genética , Genômica/métodos , Saccharomyces cerevisiae/genética , Animais , Linhagem Celular , Coronavirus/patogenicidade , Recombinação Homóloga , Coronavírus da Síndrome Respiratória do Oriente Médio/genética , Coronavírus da Síndrome Respiratória do Oriente Médio/patogenicidade
13.
Sci Rep ; 10(1): 14179, 2020 08 25.
Artigo em Inglês | MEDLINE | ID: mdl-32843695

RESUMO

A novel coronavirus (SARS-CoV-2) emerged from China in late 2019 and rapidly spread across the globe, infecting millions of people and generating societal disruption on a level not seen since the 1918 influenza pandemic. A safe and effective vaccine is desperately needed to prevent the continued spread of SARS-CoV-2; yet, rational vaccine design efforts are currently hampered by the lack of knowledge regarding viral epitopes targeted during an immune response, and the need for more in-depth knowledge on betacoronavirus immunology. To that end, we developed a computational workflow using a series of open-source algorithms and webtools to analyze the proteome of SARS-CoV-2 and identify putative T cell and B cell epitopes. Utilizing a set of stringent selection criteria to filter peptide epitopes, we identified 41 T cell epitopes (5 HLA class I, 36 HLA class II) and 6 B cell epitopes that could serve as promising targets for peptide-based vaccine development against this emerging global pathogen. To our knowledge, this is the first study to comprehensively analyze all 10 (structural, non-structural and accessory) proteins from SARS-CoV-2 using predictive algorithms to identify potential targets for vaccine development.


Assuntos
Betacoronavirus/imunologia , Biologia Computacional , Infecções por Coronavirus/imunologia , Infecções por Coronavirus/virologia , Epitopos de Linfócito B/imunologia , Epitopos de Linfócito T/imunologia , Interações Hospedeiro-Patógeno/imunologia , Pneumonia Viral/imunologia , Pneumonia Viral/virologia , Proteínas Virais/imunologia , Sequência de Aminoácidos , Linfócitos B/imunologia , Linfócitos B/metabolismo , Betacoronavirus/classificação , Betacoronavirus/genética , Betacoronavirus/metabolismo , Biologia Computacional/métodos , Infecções por Coronavirus/metabolismo , Epitopos de Linfócito B/química , Epitopos de Linfócito T/química , Genoma Viral , Genômica/métodos , Humanos , Modelos Moleculares , Pandemias , Peptídeos/química , Peptídeos/imunologia , Filogenia , Pneumonia Viral/metabolismo , Relação Estrutura-Atividade , Linfócitos T/imunologia , Linfócitos T/metabolismo , Vacinas de Subunidades/imunologia , Proteínas Virais/química , Vacinas Virais/imunologia
14.
Nat Commun ; 11(1): 4070, 2020 08 13.
Artigo em Inglês | MEDLINE | ID: mdl-32792502

RESUMO

Human astroviruses are small non-enveloped viruses with positive-sense single-stranded RNA genomes. Astroviruses cause acute gastroenteritis in children worldwide and have been associated with encephalitis and meningitis in immunocompromised individuals. It is still unknown how astrovirus particles exit infected cells following replication. Through comparative genomic analysis and ribosome profiling we here identify and confirm the expression of a conserved alternative-frame ORF, encoding the protein XP. XP-knockout astroviruses are attenuated and pseudo-revert on passaging. Further investigation into the function of XP revealed plasma and trans Golgi network membrane-associated roles in virus assembly and/or release through a viroporin-like activity. XP-knockout replicons have only a minor replication defect, demonstrating the role of XP at late stages of infection. The discovery of XP advances our knowledge of these important human viruses and opens an additional direction of research into their life cycle and pathogenesis.


Assuntos
Canais Iônicos/metabolismo , Mamastrovirus/metabolismo , Proteínas não Estruturais Virais/metabolismo , Animais , Linhagem Celular , Cricetinae , Eletroforese em Gel de Poliacrilamida , Genômica/métodos , Células HeLa , Humanos , Immunoblotting , Imunoprecipitação , Canais Iônicos/genética , Mamastrovirus/genética , Microscopia de Fluorescência , Plasmídeos/genética , Ribossomos , Proteínas não Estruturais Virais/genética , Replicação Viral/genética , Replicação Viral/fisiologia
15.
Value Health ; 23(7): 898-906, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-32762992

RESUMO

OBJECTIVES: We evaluated how next generation sequencing (NGS) can modify care pathways in an observational impact study in France. METHODS: All patients with lung cancer, colorectal cancer, or melanoma who had NGS analyses of somatic genomic alterations done in 1 of 7 biomolecular platforms certified by the French National Cancer Institute (INCa) between 2013 and 2016 were eligible. We compared patients' pathways before and after their NGS results. Endpoints consisted of the turnaround time in obtaining results, the number of patients with at least 1 genomic alteration identified, the number of actionable alterations, the impact of the genomic multidisciplinary tumor board on care pathways, the number of changes in the treatment plan, and the survival outcome up to 1 year after NGS analyses. RESULTS: 1213 patients with a request for NGS analysis were included. NGS was performed for 1155 patients, identified at least 1 genomic alteration for 867 (75%), and provided an actionable alteration for 614 (53%). Turnaround time between analyses and results was on average 8 days (Min: 0; Max: 95) for all cancer types. Before NGS analysis, 33 of 614 patients (5%) were prescribed a targeted therapy compared with 54 of 614 patients (8%) after NGS analysis. Proposition of inclusion in clinical trials with experimental treatments increased from 5% (n = 31 of 614) before to 28% (n = 178 of 614) after NGS analysis. Patients who benefited from a genotype matched treatment after NGS analysis tended to have a better survival outcome at 1 year than patients with nonmatched treatment: 258 days (±107) compared with 234 days (±106), (P = .41). CONCLUSIONS: NGS analyses resulted in a change in patients' care pathways for 20% of patients (n = 232 of 1155).


Assuntos
Neoplasias Colorretais/genética , Sequenciamento de Nucleotídeos em Larga Escala/métodos , Neoplasias Pulmonares/genética , Melanoma/genética , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Neoplasias Colorretais/terapia , Feminino , França , Genômica/métodos , Acesso aos Serviços de Saúde , Humanos , Neoplasias Pulmonares/terapia , Masculino , Melanoma/terapia , Pessoa de Meia-Idade , Terapia de Alvo Molecular , Estudos Retrospectivos , Sobrevida , Fatores de Tempo , Adulto Jovem
16.
Nat Commun ; 11(1): 3320, 2020 07 03.
Artigo em Inglês | MEDLINE | ID: mdl-32620776

RESUMO

Benthic diatoms are the main primary producers in shallow freshwater and coastal environments, fulfilling important ecological functions such as nutrient cycling and sediment stabilization. However, little is known about their evolutionary adaptations to these highly structured but heterogeneous environments. Here, we report a reference genome for the marine biofilm-forming diatom Seminavis robusta, showing that gene family expansions are responsible for a quarter of all 36,254 protein-coding genes. Tandem duplications play a key role in extending the repertoire of specific gene functions, including light and oxygen sensing, which are probably central for its adaptation to benthic habitats. Genes differentially expressed during interactions with bacteria are strongly conserved in other benthic diatoms while many species-specific genes are strongly upregulated during sexual reproduction. Combined with re-sequencing data from 48 strains, our results offer insights into the genetic diversity and gene functions in benthic diatoms.


Assuntos
Adaptação Fisiológica/genética , Diatomáceas/genética , Ecossistema , Evolução Molecular , Genoma/genética , Diatomáceas/classificação , Diatomáceas/metabolismo , Água Doce , Tamanho do Genoma , Genômica/métodos , Polimorfismo de Nucleotídeo Único , Água do Mar , Especificidade da Espécie , Transcriptoma/genética
17.
Nucleic Acids Res ; 48(14): 7681-7689, 2020 08 20.
Artigo em Inglês | MEDLINE | ID: mdl-32619234

RESUMO

Genome-enabled approaches to molecular epidemiology have become essential to public health agencies and the microbial research community. We developed the algorithm STing to provide turn-key solutions for molecular typing and gene detection directly from next generation sequence data of microbial pathogens. Our implementation of STing uses an innovative k-mer search strategy that eliminates the computational overhead associated with the time-consuming steps of quality control, assembly, and alignment, required by more traditional methods. We compared STing to six of the most widely used programs for genome-based molecular typing and demonstrate its ease of use, accuracy, speed and efficiency. STing shows superior accuracy and performance for standard multilocus sequence typing schemes, along with larger genome-scale typing schemes, and it enables rapid automated detection of antimicrobial resistance and virulence factor genes. STing determines the sequence type of traditional 7-gene MLST with 100% accuracy in less than 10 seconds per isolate. We hope that the adoption of STing will help to democratize microbial genomics and thereby maximize its benefit for public health.


Assuntos
Algoritmos , Sequenciamento de Nucleotídeos em Larga Escala , Tipagem de Sequências Multilocus/métodos , Resistência Microbiana a Medicamentos/genética , Genes Microbianos , Genômica/métodos , Software , Fatores de Virulência/genética
18.
BMC Bioinformatics ; 21(1): 272, 2020 Jul 01.
Artigo em Inglês | MEDLINE | ID: mdl-32611376

RESUMO

BACKGROUND: Chromatin 3D conformation plays important roles in regulating gene or protein functions. High-throughout chromosome conformation capture (3C)-based technologies, such as Hi-C, have been exploited to acquire the contact frequencies among genomic loci at genome-scale. Various computational tools have been proposed to recover the underlying chromatin 3D structures from in situ Hi-C contact map data. As connected residuals in a polymer, neighboring genomic loci have intrinsic mutual dependencies in building a 3D conformation. However, current methods seldom take this feature into account. RESULTS: We present a method called ShNeigh, which combines the classical MDS technique with local dependence of neighboring loci modeled by a Gaussian formula, to infer the best 3D structure from noisy and incomplete contact frequency matrices. We validated ShNeigh by comparing it to two typical distance-based algorithms, ShRec3D and ChromSDE. The comparison results on simulated Hi-C dataset showed that, while keeping the high-speed nature of classical MDS, ShNeigh can recover the true structure better than ShRec3D and ChromSDE. Meanwhile, ShNeigh is more robust to data noise. On the publicly available human GM06990 Hi-C data, we demonstrated that the structures reconstructed by ShNeigh are more reproducible between different restriction enzymes than by ShRec3D and ChromSDE, especially at high resolutions manifested by sparse contact maps, which means ShNeigh is more robust to signal coverage. CONCLUSIONS: Our method can recover stable structures in high noise and sparse signal settings. It can also reconstruct similar structures from Hi-C data obtained using different restriction enzymes. Therefore, our method provides a new direction for enhancing the reconstruction quality of chromatin 3D structures.


Assuntos
Cromatina/química , Genômica/métodos , Algoritmos , Cromossomos/química , Cromossomos/genética , Loci Gênicos , Humanos , Conformação Molecular , Interface Usuário-Computador
19.
PLoS One ; 15(7): e0235748, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32701977

RESUMO

With advances in sequencing technology, a vast amount of genomic sequence information has become available. However, annotating biological functions particularly of non-protein-coding regions in genome sequences without experiments is still a challenging task. Recently deep learning-based methods were shown to have the ability to predict gene regulatory regions from genome sequences, promising to aid the interpretation of genomic sequence data. Here, we report an improvement of the prediction accuracy for gene regulatory regions by using the design of convolution layers that efficiently process genomic sequence information, and developed a software, DeepGMAP, to train and compare different deep learning-based models (https://github.com/koonimaru/DeepGMAP). First, we demonstrate that our convolution layers, termed forward- and reverse-sequence scan (FRSS) layers, integrate both forward and reverse strand information, and enhance the power to predict gene regulatory regions. Second, we assessed previous studies and identified problems associated with data structures that caused overfitting. Finally, we introduce visualization methods to examine what the program learned. Together, our FRSS layers improve the prediction accuracy for gene regulatory regions.


Assuntos
DNA/análise , Genoma , Genômica/métodos , Redes Neurais de Computação , Sequências Reguladoras de Ácido Nucleico , Análise de Sequência de DNA/métodos , Software , Animais , DNA/genética , Humanos , Camundongos
20.
Virus Res ; 287: 198098, 2020 10 02.
Artigo em Inglês | MEDLINE | ID: mdl-32687861

RESUMO

To investigate the evolutionary and epidemiological dynamics of the current COVID-19 outbreak, a total of 112 genomes of SARS-CoV-2 strains sampled from China and 12 other countries with sampling dates between 24 December 2019 and 9 February 2020 were analyzed. We performed phylogenetic, split network, likelihood-mapping, model comparison, and phylodynamic analyses of the genomes. Based on Bayesian time-scaled phylogenetic analysis with the best-fitting combination models, we estimated the time to the most recent common ancestor (TMRCA) and evolutionary rate of SARS-CoV-2 to be 12 November 2019 (95 % BCI: 11 October 2019 and 09 December 2019) and 9.90 × 10-4 substitutions per site per year (95 % BCI: 6.29 × 10-4-1.35 × 10-3), respectively. Notably, the very low Re estimates of SARS-CoV-2 during the recent sampling period may be the result of the successful control of the pandemic in China due to extreme societal lockdown efforts. Our results emphasize the importance of using phylodynamic analyses to provide insights into the roles of various interventions to limit the spread of SARS-CoV-2 in China and beyond.


Assuntos
Betacoronavirus/classificação , Betacoronavirus/genética , Infecções por Coronavirus/epidemiologia , Infecções por Coronavirus/virologia , Genoma Viral , Genômica , Filogenia , Pneumonia Viral/epidemiologia , Pneumonia Viral/virologia , China/epidemiologia , Surtos de Doenças , Evolução Molecular , Genômica/métodos , Humanos , Pandemias
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