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1.
Sci Immunol ; 5(49)2020 07 10.
Artigo em Inglês | MEDLINE | ID: mdl-32651212

RESUMO

Although most SARS-CoV-2-infected individuals experience mild coronavirus disease 2019 (COVID-19), some patients suffer from severe COVID-19, which is accompanied by acute respiratory distress syndrome and systemic inflammation. To identify factors driving severe progression of COVID-19, we performed single-cell RNA-seq using peripheral blood mononuclear cells (PBMCs) obtained from healthy donors, patients with mild or severe COVID-19, and patients with severe influenza. Patients with COVID-19 exhibited hyper-inflammatory signatures across all types of cells among PBMCs, particularly up-regulation of the TNF/IL-1ß-driven inflammatory response as compared to severe influenza. In classical monocytes from patients with severe COVID-19, type I IFN response co-existed with the TNF/IL-1ß-driven inflammation, and this was not seen in patients with milder COVID-19. Interestingly, we documented type I IFN-driven inflammatory features in patients with severe influenza as well. Based on this, we propose that the type I IFN response plays a pivotal role in exacerbating inflammation in severe COVID-19.


Assuntos
Betacoronavirus/genética , Betacoronavirus/imunologia , Infecções por Coronavirus/imunologia , Imunofenotipagem , Vírus da Influenza A/imunologia , Influenza Humana/imunologia , Interferon Tipo I/metabolismo , Pneumonia Viral/imunologia , Índice de Gravidade de Doença , Adulto , Idoso , Idoso de 80 Anos ou mais , Linfócitos T CD8-Positivos/imunologia , Células Cultivadas , Infecções por Coronavirus/sangue , Infecções por Coronavirus/virologia , Feminino , Voluntários Saudáveis , Humanos , Inflamação/imunologia , Influenza Humana/sangue , Influenza Humana/virologia , Interleucina-1beta/metabolismo , Masculino , Pessoa de Meia-Idade , Pandemias , Pneumonia Viral/sangue , Pneumonia Viral/virologia , RNA-Seq , Análise de Célula Única , Transcriptoma , Fator de Necrose Tumoral alfa/metabolismo
2.
J Immunother Cancer ; 8(2)2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-32675312

RESUMO

BACKGROUND: Pandemic COVID-19 by severe acute respiratory syndrome (SARS) coronavirus 2 (SARS-CoV-2) infection is facilitated by the ACE2 receptor and protease TMPRSS2. Modestly sized case series have described clinical factors associated with COVID-19, while ACE2 and TMPRSS2 expression analyses have been described in some cell types. Patients with cancer may have worse outcomes to COVID-19. METHODS: We performed an integrated study of ACE2 and TMPRSS2 gene expression across and within organ systems, by normal versus tumor, across several existing databases (The Cancer Genome Atlas, Census of Immune Single Cell Expression Atlas, The Human Cell Landscape, and more). We correlated gene expression with clinical factors (including but not limited to age, gender, race, body mass index, and smoking history), HLA genotype, immune gene expression patterns, cell subsets, and single-cell sequencing as well as commensal microbiome. RESULTS: Matched normal tissues generally display higher ACE2 and TMPRSS2 expression compared with cancer, with normal and tumor from digestive organs expressing the highest levels. No clinical factors were consistently identified to be significantly associated with gene expression levels though outlier organ systems were observed for some factors. Similarly, no HLA genotypes were consistently associated with gene expression levels. Strong correlations were observed between ACE2 expression levels and multiple immune gene signatures including interferon-stimulated genes and the T cell-inflamed phenotype as well as inverse associations with angiogenesis and transforming growth factor-ß signatures. ACE2 positively correlated with macrophage subsets across tumor types. TMPRSS2 was less associated with immune gene expression but was strongly associated with epithelial cell abundance. Single-cell sequencing analysis across nine independent studies demonstrated little to no ACE2 or TMPRSS2 expression in lymphocytes or macrophages. ACE2 and TMPRSS2 gene expression associated with commensal microbiota in matched normal tissues particularly from colorectal cancers, with distinct bacterial populations showing strong associations. CONCLUSIONS: We performed a large-scale integration of ACE2 and TMPRSS2 gene expression across clinical, genetic, and microbiome domains. We identify novel associations with the microbiota and confirm host immunity associations with gene expression. We suggest caution in interpretation regarding genetic associations with ACE2 expression suggested from smaller case series.


Assuntos
Betacoronavirus/imunologia , Infecções por Coronavirus/imunologia , Neoplasias/imunologia , Peptidil Dipeptidase A/metabolismo , Pneumonia Viral/imunologia , Serina Endopeptidases/metabolismo , Idoso , Infecções por Coronavirus/epidemiologia , Infecções por Coronavirus/virologia , Conjuntos de Dados como Assunto , Feminino , Microbioma Gastrointestinal/imunologia , Regulação Neoplásica da Expressão Gênica/imunologia , Antígenos HLA/sangue , Antígenos HLA/imunologia , Humanos , Macrófagos/imunologia , Masculino , Pessoa de Meia-Idade , Neoplasias/sangue , Neoplasias/microbiologia , Neoplasias/patologia , Pandemias , Pneumonia Viral/epidemiologia , Pneumonia Viral/virologia , RNA-Seq
3.
Int J Med Sci ; 17(11): 1522-1531, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32669955

RESUMO

The outbreak of pneumonia caused by SARS-CoV-2 posed a great threat to global human health, which urgently requires us to understand comprehensively the mechanism of SARS-CoV-2 infection. Angiotensin-converting enzyme 2 (ACE2) was identified as a functional receptor for SARS-CoV-2, distribution of which may indicate the risk of different human organs vulnerable to SARS-CoV-2 infection. Previous studies investigating the distribution of ACE2 mRNA in human tissues only involved a limited size of the samples and a lack of determination for ACE2 protein. Given the heterogeneity among humans, the datasets covering more tissues with a larger size of samples should be analyzed. Indeed, ACE2 is a membrane and secreted protein, while the expression of ACE2 in blood and common blood cells remains unknown. Herein, the proteomic data in HIPED and the antibody-based immunochemistry result in HPA were collected to analyze the distribution of ACE2 protein in human tissues. The bulk RNA-seq profiles from three separate public datasets including HPA tissue Atlas, GTEx, and FANTOM5 CAGE were also obtained to determine the expression of ACE2 in human tissues. Moreover, the abundance of ACE2 in human blood and blood cells was determined by analyzing the data in the PeptideAtlas and the HPA Blood Atlas. We found that the mRNA expression cannot reflect the abundance of ACE2 factor due to the strong differences between mRNA and protein quantities of ACE2 within and across tissues. Our results suggested that ACE2 protein is mainly expressed in the small intestine, kidney, gallbladder, and testis, while the abundance of which in brain-associated tissues and blood common cells is low. HIPED revealed enrichment of ACE2 protein in the placenta and ovary despite a low mRNA level. Further, human secretome shows that the average concentration of ACE2 protein in the plasma of males is higher than those in females. Our research will be beneficial for understanding the transmission routes and sex-based differences in susceptibility of SARS-CoV-2 infection.


Assuntos
Infecções por Coronavirus/metabolismo , Peptidil Dipeptidase A/metabolismo , Pneumonia Viral/metabolismo , Receptores Virais/metabolismo , Betacoronavirus , Bases de Dados de Proteínas , Feminino , Humanos , Imuno-Histoquímica , Masculino , Espectrometria de Massas , Pandemias , Proteômica , RNA Mensageiro/metabolismo , RNA-Seq , Distribuição Tecidual , Transcriptoma
4.
Nat Med ; 26(7): 1070-1076, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-32514174

RESUMO

There is an urgent need to better understand the pathophysiology of Coronavirus disease 2019 (COVID-19), the global pandemic caused by SARS-CoV-2, which has infected more than three million people worldwide1. Approximately 20% of patients with COVID-19 develop severe disease and 5% of patients require intensive care2. Severe disease has been associated with changes in peripheral immune activity, including increased levels of pro-inflammatory cytokines3,4 that may be produced by a subset of inflammatory monocytes5,6, lymphopenia7,8 and T cell exhaustion9,10. To elucidate pathways in peripheral immune cells that might lead to immunopathology or protective immunity in severe COVID-19, we applied single-cell RNA sequencing (scRNA-seq) to profile peripheral blood mononuclear cells (PBMCs) from seven patients hospitalized for COVID-19, four of whom had acute respiratory distress syndrome, and six healthy controls. We identify reconfiguration of peripheral immune cell phenotype in COVID-19, including a heterogeneous interferon-stimulated gene signature, HLA class II downregulation and a developing neutrophil population that appears closely related to plasmablasts appearing in patients with acute respiratory failure requiring mechanical ventilation. Importantly, we found that peripheral monocytes and lymphocytes do not express substantial amounts of pro-inflammatory cytokines. Collectively, we provide a cell atlas of the peripheral immune response to severe COVID-19.


Assuntos
Betacoronavirus/imunologia , Infecções por Coronavirus , Imunidade Celular , Leucócitos Mononucleares , Pandemias , Pneumonia Viral , Análise de Sequência de RNA/métodos , Análise de Célula Única/métodos , Adulto , Idoso , Idoso de 80 Anos ou mais , Estudos de Casos e Controles , Infecções por Coronavirus/genética , Infecções por Coronavirus/imunologia , Infecções por Coronavirus/patologia , Citocinas/genética , Citocinas/metabolismo , Feminino , Perfilação da Expressão Gênica/métodos , Humanos , Células Matadoras Naturais/imunologia , Células Matadoras Naturais/metabolismo , Leucócitos Mononucleares/imunologia , Leucócitos Mononucleares/metabolismo , Leucócitos Mononucleares/virologia , Masculino , Pessoa de Meia-Idade , Pneumonia Viral/genética , Pneumonia Viral/imunologia , Pneumonia Viral/patologia , RNA-Seq/métodos , Índice de Gravidade de Doença , Linfócitos T/imunologia , Linfócitos T/metabolismo , Adulto Jovem
5.
Fertil Steril ; 113(6): 1135-1139, 2020 06.
Artigo em Inglês | MEDLINE | ID: mdl-32482249

RESUMO

OBJECTIVE: To describe detection of severe acute respiratory syndrome (SARS)-coronavirus 2 (CoV-2) in seminal fluid of patients recovering from coronavirus disease 2019 (COVID-19) and to describe the expression profile of angiotensin-converting enzyme 2 (ACE2) and Transmembrane Serine Protease 2 (TMPRSS2) within the testicle. DESIGN: Observational, cross-sectional study. SETTING: Tertiary referral center. PATIENT(S): Thirty-four adult Chinese males diagnosed with COVID-19 through confirmatory quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR) from pharyngeal swab samples. INTERVENTION(S): None. MAIN OUTCOME MEASURE(S): Identification of SARS-CoV-2 on qRT-PCR of single ejaculated semen samples. Semen quality was not assessed. Expression patterns of ACE2 and TMPRSS2 in the human testis are explored through previously published single-cell transcriptome datasets. RESULT(S): Six patients (19%) demonstrated scrotal discomfort suggestive of viral orchitis around the time of COVID-19 confirmation. Severe acute respiratory syndrome-CoV-2 was not detected in semen after a median of 31 days (interquartile range, 29-36 days) from COVID-19 diagnosis. Single-cell transcriptome analysis demonstrates sparse expression of ACE2 and TMPRSS2, with almost no overlapping gene expression. CONCLUSION(S): Severe acute respiratory syndrome-CoV-2 was not detected in the semen of patients recovering from COVID-19 1 month after COVID-19 diagnosis. Angiotensin-converting enzyme 2-mediated viral entry of SARS-CoV-2 into target host cells is unlikely to occur within the human testicle based on ACE2 and TMPRSS2 expression. The long-term effects of SARS-CoV-2 on male reproductive function remain unknown.


Assuntos
Betacoronavirus/isolamento & purificação , Infecções por Coronavirus/virologia , Pneumonia Viral/virologia , Sêmen/virologia , Adolescente , Adulto , Betacoronavirus/genética , Técnicas de Laboratório Clínico , Infecções por Coronavirus/diagnóstico , Infecções por Coronavirus/enzimologia , Infecções por Coronavirus/genética , Estudos Transversais , Humanos , Masculino , Pessoa de Meia-Idade , Pandemias , Peptidil Dipeptidase A/genética , Pneumonia Viral/diagnóstico , Pneumonia Viral/enzimologia , Pneumonia Viral/genética , RNA-Seq , Reação em Cadeia da Polimerase em Tempo Real , Serina Endopeptidases/genética , Testículo/enzimologia , Testículo/virologia , Fatores de Tempo , Transcriptoma , Internalização do Vírus , Adulto Jovem
6.
BMC Bioinformatics ; 21(1): 214, 2020 May 26.
Artigo em Inglês | MEDLINE | ID: mdl-32456667

RESUMO

BACKGROUND: Mounting evidence suggests several diseases and biological processes target transcription termination to misregulate gene expression. Disruption of transcription termination leads to readthrough transcription past the 3' end of genes, which can result in novel transcripts, changes in epigenetic states and altered 3D genome structure. RESULTS: We developed Automatic Readthrough Transcription Detection (ARTDeco), a tool to detect and analyze multiple features of readthrough transcription from RNA-seq and other next-generation sequencing (NGS) assays that profile transcriptional activity. ARTDeco robustly quantifies the global severity of readthrough phenotypes, and reliably identifies individual genes that fail to terminate (readthrough genes), are aberrantly transcribed due to upstream termination failure (read-in genes), and novel transcripts created as a result of readthrough (downstream of gene or DoG transcripts). We used ARTDeco to characterize readthrough transcription observed during influenza A virus (IAV) infection, validating its specificity and sensitivity by comparing its performance in samples infected with a mutant virus that fails to block transcription termination. We verify ARTDeco's ability to detect readthrough as well as identify read-in genes from different experimental assays across multiple experimental systems with known defects in transcriptional termination, and show how these results can be leveraged to improve the interpretation of gene expression and downstream analysis. Applying ARTDeco to a gene expression data set from IAV-infected monocytes from different donors, we find strong evidence that read-in gene-associated expression quantitative trait loci (eQTLs) likely regulate genes upstream of read-in genes. This indicates that taking readthrough transcription into account is important for the interpretation of eQTLs in systems where transcription termination is blocked. CONCLUSIONS: ARTDeco aids researchers investigating readthrough transcription in a variety of systems and contexts.


Assuntos
Software , Transcrição Genética , Regulação da Expressão Gênica , Sequenciamento de Nucleotídeos em Larga Escala , Humanos , Vírus da Influenza A/fisiologia , Monócitos/metabolismo , Monócitos/virologia , Locos de Características Quantitativas , RNA-Seq , Terminação da Transcrição Genética
7.
BMC Bioinformatics ; 21(1): 221, 2020 May 29.
Artigo em Inglês | MEDLINE | ID: mdl-32471392

RESUMO

BACKGROUND: The use of RNA-sequencing (RNA-seq) in molecular biology research and clinical settings has increased significantly over the past decade. Despite its widespread adoption, there is a lack of simple and interactive tools to analyze and explore RNA-seq data. Many established tools require programming or Unix/Bash knowledge to analyze and visualize results. This requirement presents a significant barrier for many researchers to efficiently analyze and present RNA-seq data. RESULTS: Here we present BEAVR, a Browser-based tool for the Exploration And Visualization of RNA-seq data. BEAVR is an easy-to-use tool that facilitates interactive analysis and exploration of RNA-seq data. BEAVR is developed in R and uses DESeq2 as its engine for differential gene expression (DGE) analysis, but assumes users have no prior knowledge of R or DESeq2. BEAVR allows researchers to easily obtain a table of differentially-expressed genes with statistical testing and then visualize the results in a series of graphs, plots and heatmaps. Users are able to customize many parameters for statistical testing, dealing with variance, clustering methods and pathway analysis to generate high quality figures. CONCLUSION: BEAVR simplifies analysis for novice users but also streamlines the RNA-seq analysis process for experts by automating several steps. BEAVR and its documentation can be found on GitHub at https://github.com/developerpiru/BEAVR. BEAVR is available as a Docker container at https://hub.docker.com/r/pirunthan/beavr.


Assuntos
RNA-Seq/métodos , Software , Análise por Conglomerados , Gráficos por Computador , Interpretação Estatística de Dados , Humanos
8.
Parasitol Res ; 119(7): 2351-2358, 2020 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-32451717

RESUMO

Naegleria fowleri causes a deadly infection known as primary amoebic meningoencephalitis (PAM). To our knowledge, there are very few transcriptome studies conducted on these brain-eating amoebae, despite rise in the number of cases. Although the Naegleria genome has been sequenced, currently, it is not well annotated. Transcriptome level studies are needed to help understand the pathology and biology of this fatal parasitic infection. Recently, we showed that nanoparticles loaded with the flavonoid Hesperidin (HDN) are potential novel antimicrobial agents. N. fowleri trophozoites were treated with and without HDN-conjugated with silver nanoparticles (AgNPs) and silver only, and then, 50% minimum inhibitory concentration (MIC) was determined. The results revealed that the MIC of HDN-conjugated AgNPs was 12.5 microg/mL when treated for 3 h. As no reference genome exists for N. fowleri, de novo RNA transcriptome analysis using RNA-Seq and differential gene expression analysis was performed using the Trinity software. Analysis revealed that more than 2000 genes were differentially expressed in response to N. fowleri treatment with HDN-conjugated AgNPs. Some of the genes were linked to oxidative stress response, DNA repair, cell division, cell signalling and protein synthesis. The downregulated genes were linked with processes such as protein modification, synthesis of aromatic amino acids, when compared with untreated N. fowleri. Further transcriptome studies will lead to understanding of genetic mechanisms of the biology and pathogenesis and/or the identification of much needed drug candidates.


Assuntos
Infecções Protozoárias do Sistema Nervoso Central/parasitologia , Hesperidina/farmacocinética , Naegleria fowleri/genética , Prata/farmacologia , Transcriptoma/genética , Animais , Divisão Celular/genética , Reparo do DNA/genética , Perfilação da Expressão Gênica , Hesperidina/metabolismo , Humanos , Nanopartículas Metálicas , Estresse Oxidativo/genética , Testes de Sensibilidade Parasitária , RNA-Seq , Prata/metabolismo
9.
PLoS Genet ; 16(5): e1008754, 2020 05.
Artigo em Inglês | MEDLINE | ID: mdl-32365093

RESUMO

FSHD is characterized by the misexpression of DUX4 in skeletal muscle. Although DUX4 upregulation is thought to be the pathogenic cause of FSHD, DUX4 is lowly expressed in patient samples, and analysis of the consequences of DUX4 expression has largely relied on artificial overexpression. To better understand the native expression profile of DUX4 and its targets, we performed bulk RNA-seq on a 6-day differentiation time-course in primary FSHD2 patient myoblasts. We identify a set of 54 genes upregulated in FSHD2 cells, termed FSHD-induced genes. Using single-cell and single-nucleus RNA-seq on myoblasts and differentiated myotubes, respectively, we captured, for the first time, DUX4 expressed at the single-nucleus level in a native state. We identified two populations of FSHD myotube nuclei based on low or high enrichment of DUX4 and FSHD-induced genes ("FSHD-Lo" and "FSHD Hi", respectively). FSHD-Hi myotube nuclei coexpress multiple DUX4 target genes including DUXA, LEUTX and ZSCAN4, and also upregulate cell cycle-related genes with significant enrichment of E2F target genes and p53 signaling activation. We found more FSHD-Hi nuclei than DUX4-positive nuclei, and confirmed with in situ RNA/protein detection that DUX4 transcribed in only one or two nuclei is sufficient for DUX4 protein to activate target genes across multiple nuclei within the same myotube. DUXA (the DUX4 paralog) is more widely expressed than DUX4, and depletion of DUXA suppressed the expression of LEUTX and ZSCAN4 in late, but not early, differentiation. The results suggest that the DUXA can take over the role of DUX4 to maintain target gene expression. These results provide a possible explanation as to why it is easier to detect DUX4 target genes than DUX4 itself in patient cells and raise the possibility of a self-sustaining network of gene dysregulation triggered by the limited DUX4 expression.


Assuntos
Núcleo Celular/metabolismo , Fibras Musculares Esqueléticas/metabolismo , Distrofia Muscular Facioescapuloumeral , RNA-Seq/métodos , Análise de Célula Única/métodos , Estudos de Casos e Controles , Diferenciação Celular , Núcleo Celular/química , Núcleo Celular/classificação , Núcleo Celular/patologia , Células Cultivadas , Regulação da Expressão Gênica , Células HEK293 , Humanos , Proteínas dos Microfilamentos/genética , Proteínas dos Microfilamentos/metabolismo , Fibras Musculares Esqueléticas/patologia , Fibras Musculares Esqueléticas/fisiologia , Fibras Musculares Esqueléticas/ultraestrutura , Distrofia Muscular Facioescapuloumeral/genética , Distrofia Muscular Facioescapuloumeral/metabolismo , Distrofia Muscular Facioescapuloumeral/patologia , Mioblastos/metabolismo , Mioblastos/fisiologia , Proteínas Nucleares/genética , Proteínas Nucleares/metabolismo , Proteínas de Ligação a RNA/genética , Proteínas de Ligação a RNA/metabolismo , Sequenciamento Completo do Exoma
10.
PLoS One ; 15(5): e0232011, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32374731

RESUMO

Nitrogen (N) is critical to the growth and productivity of crops. To understand the molecular mechanisms influenced by N stress, we used RNA-Sequencing (RNA-Seq) to analyze differentially expressed genes (DEGs) in root and leaf tissues of spinach. N stress negatively influenced photosynthesis, biomass accumulation, amino acid profiles, and partitioning of N across tissues. RNA-seq analysis revealed that N stress caused most transcriptomic changes in roots, identifying 1,346 DEGs. High-affinity nitrate transporters (NRT2.1, NRT2.5) and glutamine amidotransferase (GAT1) genes were strongly induced in roots in response to N deplete and replete conditions, respectively. GO and KEGG analyses revealed that the functions associated with metabolic pathways and nutrient reservoir activity were enriched due to N stress. Whereas KEGG pathway enrichment analysis indicated the upregulation of DEGs associated with DNA replication, pyrimidine, and purine metabolism in the presence of high N in leaf tissue. A subset of transcription factors comprising bHLH, MYB, WRKY, and AP2/ERF family members was over-represented in both tissues in response to N perturbation. Interesting DEGs associated with N uptake, amino acid metabolism, hormonal pathway, carbon metabolism, along with transcription factors, were highlighted. The results provide valuable information about the underlying molecular processes in response to N stress in spinach and; could serve as a resource for functional analysis of candidate genes/pathways and enhancement of nitrogen use efficiency.


Assuntos
Nitrogênio/metabolismo , Spinacia oleracea/genética , Spinacia oleracea/metabolismo , Estresse Fisiológico/genética , Transcriptoma , Perfilação da Expressão Gênica , Regulação da Expressão Gênica de Plantas/efeitos dos fármacos , Redes e Vias Metabólicas/efeitos dos fármacos , Redes e Vias Metabólicas/genética , Nitrogênio/deficiência , Nitrogênio/farmacologia , Especificidade de Órgãos/efeitos dos fármacos , Especificidade de Órgãos/genética , Fotossíntese/efeitos dos fármacos , Fotossíntese/genética , Folhas de Planta/efeitos dos fármacos , Folhas de Planta/genética , Folhas de Planta/metabolismo , Raízes de Plantas/efeitos dos fármacos , Raízes de Plantas/genética , Raízes de Plantas/metabolismo , RNA-Seq/métodos , Análise de Sequência de RNA/métodos , Spinacia oleracea/efeitos dos fármacos , Estresse Fisiológico/efeitos dos fármacos , Transcriptoma/efeitos dos fármacos
12.
BMC Bioinformatics ; 21(1): 198, 2020 May 19.
Artigo em Inglês | MEDLINE | ID: mdl-32429934

RESUMO

BACKGROUND: Power analysis becomes an inevitable step in experimental design of current biomedical research. Complex designs allowing diverse correlation structures are commonly used in RNA-Seq experiments. However, the field currently lacks statistical methods to calculate sample size and estimate power for RNA-Seq differential expression studies using such designs. To fill the gap, simulation based methods have a great advantage by providing numerical solutions, since theoretical distributions of test statistics are typically unavailable for such designs. RESULTS: In this paper, we propose a novel simulation based procedure for power estimation of differential expression with the employment of generalized linear mixed effects models for correlated expression data. We also propose a new procedure for power estimation of differential expression with the use of a bivariate negative binomial distribution for paired designs. We compare the performance of both the likelihood ratio test and Wald test under a variety of simulation scenarios with the proposed procedures. The simulated distribution was used to estimate the null distribution of test statistics in order to achieve the desired false positive control and was compared to the asymptotic Chi-square distribution. In addition, we applied the procedure for paired designs to the TCGA breast cancer data set. CONCLUSIONS: In summary, we provide a framework for power estimation of RNA-Seq differential expression under complex experimental designs. Simulation results demonstrate that both the proposed procedures properly control the false positive rate at the nominal level.


Assuntos
RNA-Seq/métodos , Distribuição Binomial , Neoplasias da Mama/genética , Neoplasias da Mama/metabolismo , Distribuição de Qui-Quadrado , Feminino , Humanos , Modelos Lineares , Tamanho da Amostra
13.
PLoS One ; 15(4): e0224909, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32352970

RESUMO

Sequence count data are commonly modelled using the negative binomial (NB) distribution. Several empirical studies, however, have demonstrated that methods based on the NB-assumption do not always succeed in controlling the false discovery rate (FDR) at its nominal level. In this paper, we propose a dedicated statistical goodness of fit test for the NB distribution in regression models and demonstrate that the NB-assumption is violated in many publicly available RNA-Seq and 16S rRNA microbiome datasets. The zero-inflated NB distribution was not found to give a substantially better fit. We also show that the NB-based tests perform worse on the features for which the NB-assumption was violated than on the features for which no significant deviation was detected. This gives an explanation for the poor behaviour of NB-based tests in many published evaluation studies. We conclude that nonparametric tests should be preferred over parametric methods.


Assuntos
Distribuição Binomial , RNA-Seq/métodos , Microbiota , Distribuição de Poisson , RNA Ribossômico 16S/genética , Análise de Regressão
14.
BMC Bioinformatics ; 21(1): 171, 2020 May 01.
Artigo em Inglês | MEDLINE | ID: mdl-32357831

RESUMO

BACKGROUND: High-throughput sequencing experiments followed by differential expression analysis is a widely used approach for detecting genomic biomarkers. A fundamental step in differential expression analysis is to model the association between gene counts and covariates of interest. Existing models assume linear effect of covariates, which is restrictive and may not be sufficient for certain phenotypes. RESULTS: We introduce NBAMSeq, a flexible statistical model based on the generalized additive model and allows for information sharing across genes in variance estimation. Specifically, we model the logarithm of mean gene counts as sums of smooth functions with the smoothing parameters and coefficients estimated simultaneously within a nested iterative method. The variance is estimated by the Bayesian shrinkage approach to fully exploit the information across all genes. CONCLUSIONS: Based on extensive simulations and case studies of RNA-Seq data, we show that NBAMSeq offers improved performance in detecting nonlinear effect and maintains equivalent performance in detecting linear effect compared to existing methods. The vignette and source code of NBAMSeq are available at http://bioconductor.org/packages/release/bioc/html/NBAMSeq.html.


Assuntos
Análise de Dados , Modelos Estatísticos , RNA-Seq , Teorema de Bayes , Simulação por Computador , Humanos , Dinâmica não Linear , Software
15.
BMC Bioinformatics ; 21(1): 206, 2020 May 24.
Artigo em Inglês | MEDLINE | ID: mdl-32448189

RESUMO

BACKGROUND: With the explosion in the number of methods designed to analyze bulk and single-cell RNA-seq data, there is a growing need for approaches that assess and compare these methods. The usual technique is to compare methods on data simulated according to some theoretical model. However, as real data often exhibit violations from theoretical models, this can result in unsubstantiated claims of a method's performance. RESULTS: Rather than generate data from a theoretical model, in this paper we develop methods to add signal to real RNA-seq datasets. Since the resulting simulated data are not generated from an unrealistic theoretical model, they exhibit realistic (annoying) attributes of real data. This lets RNA-seq methods developers assess their procedures in non-ideal (model-violating) scenarios. Our procedures may be applied to both single-cell and bulk RNA-seq. We show that our simulation method results in more realistic datasets and can alter the conclusions of a differential expression analysis study. We also demonstrate our approach by comparing various factor analysis techniques on RNA-seq datasets. CONCLUSIONS: Using data simulated from a theoretical model can substantially impact the results of a study. We developed more realistic simulation techniques for RNA-seq data. Our tools are available in the seqgendiff R package on the Comprehensive R Archive Network: https://cran.r-project.org/package=seqgendiff.


Assuntos
Simulação por Computador , Bases de Dados Genéticas , RNA-Seq , Algoritmos , Perfilação da Expressão Gênica , Humanos , Análise de Componente Principal , Software , Sequenciamento Completo do Exoma
16.
Gene ; 749: 144754, 2020 Jul 30.
Artigo em Inglês | MEDLINE | ID: mdl-32376450

RESUMO

DNA methylation is an essential epigenetic modification that significantly regulates gene expression during development and differentiation. In this study, genome-wide methylation analysis of different gonads of the large yellow croaker was performed using whole-genome bisulfite sequencing (WGBS), which has characterized DNA methylation patterns in gonad tissue and identified candidate regions for future studies. Clustering analysis revealed that male and neomale methylation patterns were close compared to female. Based on KEGG pathway analysis of differentially methylated genes, we obtained signaling pathways related to gonadal development. We further investigated the methylation status of previously reported sex determination genes, and found that these genes showed different methylation status in three types of gonads, which may provide important clues to reveal the sex determination genes in the large yellow croaker. Furthermore, combined with transcriptome analysis, we found 7 sex-related genes in three comparison groups where expression negatively correlated with methylation.


Assuntos
Metilação de DNA , Gônadas/metabolismo , Perciformes/genética , Animais , Citosina/metabolismo , Epigênese Genética , Feminino , Masculino , Perciformes/metabolismo , Regiões Promotoras Genéticas , RNA-Seq , Análise de Sequência de DNA , Processos de Determinação Sexual , Fatores de Transcrição/genética
17.
Nat Commun ; 11(1): 2156, 2020 05 01.
Artigo em Inglês | MEDLINE | ID: mdl-32358485

RESUMO

Colorectal cancer (CRC) is the most common gastrointestinal malignancy in the U.S.A. and approximately 50% of patients develop metastatic disease (mCRC). Despite our understanding of long non-coding RNAs (lncRNAs) in primary colon cancer, their role in mCRC and treatment resistance remains poorly characterized. Therefore, through transcriptome sequencing of normal, primary, and distant mCRC tissues we find 148 differentially expressed RNAs Associated with Metastasis (RAMS). We prioritize RAMS11 due to its association with poor disease-free survival and promotion of aggressive phenotypes in vitro and in vivo. A FDA-approved drug high-throughput viability assay shows that elevated RAMS11 expression increases resistance to topoisomerase inhibitors. Subsequent experiments demonstrate RAMS11-dependent recruitment of Chromobox protein 4 (CBX4) transcriptionally activates Topoisomerase II alpha (TOP2α). Overall, recent clinical trials using topoisomerase inhibitors coupled with our findings of RAMS11-dependent regulation of TOP2α supports the potential use of RAMS11 as a biomarker and therapeutic target for mCRC.


Assuntos
Neoplasias Colorretais/genética , Neoplasias Colorretais/patologia , RNA Longo não Codificante/genética , RNA Longo não Codificante/metabolismo , Animais , Western Blotting , Células CACO-2 , Linhagem Celular Tumoral , Imunoprecipitação da Cromatina , Biologia Computacional , DNA Topoisomerases Tipo II/metabolismo , Progressão da Doença , Éxons/genética , Regulação Neoplásica da Expressão Gênica/efeitos dos fármacos , Regulação Neoplásica da Expressão Gênica/genética , Células HCT116 , Células HT29 , Humanos , Ligases/metabolismo , Camundongos , Proteínas do Grupo Polycomb/metabolismo , RNA-Seq , Reação em Cadeia da Polimerase em Tempo Real , Inibidores da Topoisomerase/farmacologia
18.
PLoS One ; 15(5): e0229700, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32379829

RESUMO

One of the most important and exclusive characteristics of mycobacteria is their cell wall. Amongst its constituent components are two related families of glycosylated lipids, diphthioceranates and phthiocerol dimycocerosate (PDIM) and its variant phenolic glycolipids (PGL). PGL have been associated with cell wall impermeability, phagocytosis, defence against nitrosative and oxidative stress and, intriguingly, biofilm formation. In bacteria from the Mycobacterium tuberculosis complex (MTBC), the biosynthetic pathway of the phenolphthiocerol moiety of PGL depends upon the expression of several genes encoding type I polyketide synthases (PKS), namely ppsA-E and pks15/1 which constitute the PDIM + PGL locus, and that are highly conserved in PDIM/PGL-producing strains. Consensus has not been achieved regarding the genetic organization of pks15/1 locus and knowledge is lacking on its transcriptional signature. Here we explore publicly available datasets of transcriptome data (RNA-seq) from more than 100 MTBC experiments in 40 growth conditions to outline the transcriptional structure and signature of pks15/1, using a differential expression approach to infer the regulatory patterns involving these and related genes. We show that pks1 expression is highly correlated with fadD22, Rv2949c, lppX, fadD29 and, also, pks6 and pks12, with the first three putatively integrating into a polycistronic structure. We evidence dynamic transcriptional heterogeneity within the genes involved in phenolphtiocerol and phenolic glycolipid production, most exhibiting up-regulation upon acidic pH and antibiotic exposure and down-regulation under hypoxia, dormancy, and low/high iron concentration. We finally propose a model based on transcriptome data in which σD positively regulates pks1, pks15 and fadD22, while σB and σE factors exert negative regulation at an upper level.


Assuntos
Antígenos de Bactérias/biossíntese , Antígenos de Bactérias/genética , Proteínas de Bactérias/genética , Regulação Bacteriana da Expressão Gênica , Glicolipídeos/biossíntese , Glicolipídeos/genética , Mycobacterium tuberculosis/genética , Mycobacterium tuberculosis/patogenicidade , Policetídeo Sintases/genética , Transcriptoma , Parede Celular/metabolismo , Simulação por Computador , Redes Reguladoras de Genes , Loci Gênicos , Genoma Bacteriano/genética , Ligases/genética , RNA-Seq , Virulência/genética
19.
PLoS One ; 15(5): e0225564, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32380515

RESUMO

Senna tora is an annual herb with rich source of anthraquinones that have tremendous pharmacological properties. However, there is little mention of genetic information for this species, especially regarding the biosynthetic pathways of anthraquinones. To understand the key genes and regulatory mechanism of anthraquinone biosynthesis pathways, we performed spatial and temporal transcriptome sequencing of S. tora using short RNA sequencing (RNA-Seq) and long-read isoform sequencing (Iso-Seq) technologies, and generated two unigene sets composed of 118,635 and 39,364, respectively. A comprehensive functional annotation and classification with multiple public databases identified array of genes involved in major secondary metabolite biosynthesis pathways and important transcription factor (TF) families (MYB, MYB-related, AP2/ERF, C2C2-YABBY, and bHLH). Differential expression analysis indicated that the expression level of genes involved in anthraquinone biosynthetic pathway regulates differently depending on the degree of tissues and seeds development. Furthermore, we identified that the amount of anthraquinone compounds were greater in late seeds than early ones. In conclusion, these results provide a rich resource for understanding the anthraquinone metabolism in S. tora.


Assuntos
Antraquinonas/metabolismo , Sementes/genética , Extrato de Senna/metabolismo , Senna (Planta)/genética , Senna (Planta)/metabolismo , Transcriptoma , Regulação da Expressão Gênica de Plantas , Folhas de Planta/genética , Folhas de Planta/crescimento & desenvolvimento , Proteínas de Plantas/genética , Raízes de Plantas/genética , Raízes de Plantas/crescimento & desenvolvimento , RNA de Plantas/genética , RNA-Seq , Reação em Cadeia da Polimerase em Tempo Real , Sementes/crescimento & desenvolvimento , Fatores de Transcrição/genética
20.
PLoS One ; 15(4): e0232271, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32353015

RESUMO

Benchmarking RNA-seq differential expression analysis methods using spike-in and simulated RNA-seq data has often yielded inconsistent results. The spike-in data, which were generated from the same bulk RNA sample, only represent technical variability, making the test results less reliable. We compared the performance of 12 differential expression analysis methods for RNA-seq data, including recent variants in widely used software packages, using both RNA spike-in and simulation data for negative binomial (NB) model. Performance of edgeR, DESeq2, and ROTS was particularly different between the two benchmark tests. Then, each method was tested under most extensive simulation conditions especially demonstrating the large impacts of proportion, dispersion, and balance of differentially expressed (DE) genes. DESeq2, a robust version of edgeR (edgeR.rb), voom with TMM normalization (voom.tmm) and sample weights (voom.sw) showed an overall good performance regardless of presence of outliers and proportion of DE genes. The performance of RNA-seq DE gene analysis methods substantially depended on the benchmark used. Based on the simulation results, suitable methods were suggested under various test conditions.


Assuntos
Perfilação da Expressão Gênica/métodos , RNA-Seq/métodos , RNA/genética , Benchmarking/métodos , Simulação por Computador , Humanos , Análise de Sequência de RNA/métodos , Software
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