Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 20 de 5.153
Filtrar
1.
PLoS Comput Biol ; 16(9): e1008195, 2020 09.
Artigo em Inglês | MEDLINE | ID: mdl-32898151

RESUMO

We present VALERIE (Visualising alternative splicing events from single-cell ribonucleic acid-sequencing experiments), an R package for visualising alternative splicing events at single-cell resolution. To explore any given specified genomic region, corresponding to an alternative splicing event, VALERIE generates an ensemble of informative plots to visualise cell-to-cell heterogeneity of alternative splicing profiles across single cells and performs statistical tests to compare percent spliced-in (PSI) values across the user-defined groups of cells. Among the features available, VALERIE displays PSI values, in lieu of read coverage, which is more suitable for representing alternative splicing profiles for a large number of samples typically generated by single-cell RNA-sequencing experiments. VALERIE is available on the Comprehensive R Archive Network (CRAN): https://cran.r-project.org/web/packages/VALERIE/index.html.


Assuntos
Processamento Alternativo/genética , Análise de Sequência de RNA/métodos , Análise de Célula Única/métodos , Software , Animais , Células Cultivadas , Biologia Computacional , Camundongos
2.
PLoS Comput Biol ; 16(9): e1008205, 2020 09.
Artigo em Inglês | MEDLINE | ID: mdl-32903255

RESUMO

Single-cell RNA sequencing (scRNA-seq) can map cell types, states and transitions during dynamic biological processes such as tissue development and regeneration. Many trajectory inference methods have been developed to order cells by their progression through a dynamic process. However, when time series data is available, most of these methods do not consider the available time information when ordering cells and are instead designed to work only on a single scRNA-seq data snapshot. We present Tempora, a novel cell trajectory inference method that orders cells using time information from time-series scRNA-seq data. In performance comparison tests, Tempora inferred known developmental lineages from three diverse tissue development time series data sets, beating state of the art methods in accuracy and speed. Tempora works at the level of cell clusters (types) and uses biological pathway information to help identify cell type relationships. This approach increases gene expression signal from single cells, processing speed, and interpretability of the inferred trajectory. Our results demonstrate the utility of a combination of time and pathway information to supervise trajectory inference for scRNA-seq based analysis.


Assuntos
Biologia Computacional/métodos , Perfilação da Expressão Gênica/métodos , Análise de Sequência de RNA/métodos , Análise de Célula Única/métodos , Software , Algoritmos , Animais , Células Cultivadas , Humanos , Camundongos , Mioblastos/metabolismo , RNA/genética , RNA/metabolismo , Reprodutibilidade dos Testes
3.
Nat Commun ; 11(1): 4662, 2020 09 16.
Artigo em Inglês | MEDLINE | ID: mdl-32938926

RESUMO

Haplotype reconstruction of distant genetic variants remains an unsolved problem due to the short-read length of common sequencing data. Here, we introduce HapTree-X, a probabilistic framework that utilizes latent long-range information to reconstruct unspecified haplotypes in diploid and polyploid organisms. It introduces the observation that differential allele-specific expression can link genetic variants from the same physical chromosome, thus even enabling using reads that cover only individual variants. We demonstrate HapTree-X's feasibility on in-house sequenced Genome in a Bottle RNA-seq and various whole exome, genome, and 10X Genomics datasets. HapTree-X produces more complete phases (up to 25%), even in clinically important genes, and phases more variants than other methods while maintaining similar or higher accuracy and being up to 10×  faster than other tools. The advantage of HapTree-X's ability to use multiple lines of evidence, as well as to phase polyploid genomes in a single integrative framework, substantially grows as the amount of diverse data increases.


Assuntos
Desequilíbrio Alélico , Haplótipos , Análise de Sequência de RNA , Algoritmos , Bases de Dados Genéticas , Diploide , Humanos , Células K562 , Modelos Genéticos , Modelos Estatísticos , Polimorfismo de Nucleotídeo Único , Poliploidia , RNA-Seq , Análise de Sequência de RNA/métodos , Análise de Sequência de RNA/estatística & dados numéricos
4.
Nat Commun ; 11(1): 4364, 2020 08 31.
Artigo em Inglês | MEDLINE | ID: mdl-32868781

RESUMO

Pathophysiological roles of cardiac dopamine system remain unknown. Here, we show the role of dopamine D1 receptor (D1R)-expressing cardiomyocytes (CMs) in triggering heart failure-associated ventricular arrhythmia. Comprehensive single-cell resolution analysis identifies the presence of D1R-expressing CMs in both heart failure model mice and in heart failure patients with sustained ventricular tachycardia. Overexpression of D1R in CMs disturbs normal calcium handling while CM-specific deletion of D1R ameliorates heart failure-associated ventricular arrhythmia. Thus, cardiac D1R has the potential to become a therapeutic target for preventing heart failure-associated ventricular arrhythmia.


Assuntos
Arritmias Cardíacas/etiologia , Insuficiência Cardíaca , Miócitos Cardíacos/metabolismo , Receptores de Dopamina D1/metabolismo , Animais , Arritmias Cardíacas/prevenção & controle , Perfilação da Expressão Gênica/métodos , Humanos , Camundongos , Camundongos Transgênicos , Ratos , Receptores de Dopamina D1/genética , Análise de Sequência de RNA/métodos , Análise de Célula Única/métodos , Taquicardia Ventricular/etiologia , Taquicardia Ventricular/prevenção & controle
5.
Sci Adv ; 6(39)2020 09.
Artigo em Inglês | MEDLINE | ID: mdl-32978154

RESUMO

Detection of viruses is critical for controlling disease spread. Recent emerging viral threats, including Zika virus, Ebola virus, and SARS-CoV-2 responsible for coronavirus disease 2019 (COVID-19) highlight the cost and difficulty in responding rapidly. To address these challenges, we develop a platform for low-cost and rapid detection of viral RNA with DNA nanoswitches that mechanically reconfigure in response to specific viruses. Using Zika virus as a model system, we show nonenzymatic detection of viral RNA with selective and multiplexed detection between related viruses and viral strains. For clinical-level sensitivity in biological fluids, we paired the assay with sample preparation using either RNA extraction or isothermal preamplification. Our assay requires minimal laboratory infrastructure and is adaptable to other viruses, as demonstrated by quickly developing DNA nanoswitches to detect SARS-CoV-2 RNA in saliva. Further development and field implementation will improve our ability to detect emergent viral threats and ultimately limit their impact.


Assuntos
Betacoronavirus/genética , Infecções por Coronavirus/diagnóstico , DNA de Cadeia Simples/genética , Eletroforese em Gel de Ágar/métodos , Pneumonia Viral/diagnóstico , RNA Viral/genética , Análise de Sequência de RNA/métodos , Sequência de Bases , Linhagem Celular Tumoral , Infecções por Coronavirus/virologia , Dengue/diagnóstico , Dengue/virologia , Vírus da Dengue/genética , Eletroforese em Gel de Ágar/economia , Humanos , Limite de Detecção , Pandemias , Pneumonia Viral/virologia , Saliva/virologia , Análise de Sequência de RNA/economia , Zika virus/genética , Infecção por Zika virus/diagnóstico , Infecção por Zika virus/virologia
6.
PLoS One ; 15(8): e0231125, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32866172

RESUMO

Korean peninsula weather is rapidly becoming subtropical due to global warming. In summer 2018, South Korea experienced the highest temperatures since the meteorological observations recorded in 1907. Heat stress has a negative effect on Holstein cows, the most popular breed of dairy cattle in South Korea, which is susceptible to heat. To examine physiological changes in dairy cows under heat stress conditions, we analyzed the profiles circulating microRNAs isolated from whole blood samples collected under heat stress and non-heat stress conditions using small RNA sequencing. We compared the expression profiles in lactating cows under heat stress and non-heat stress conditions to understand the regulation of biological processes in heat-stressed cows. Moreover, we measured several heat stress indicators, such as rectal temperature, milk yield, and average daily gain. All these assessments showed that pregnant cows were more susceptible to heat stress than non-pregnant cows. In addition, we found the differential expression of 11 miRNAs (bta-miR-19a, bta-miR-19b, bta-miR-30a-5p, and several from the bta-miR-2284 family) in both pregnant and non-pregnant cows under heat stress conditions. In target gene prediction and gene set enrichment analysis, these miRNAs were found to be associated with the cytoskeleton, cell junction, vasculogenesis, cell proliferation, ATP synthesis, oxidative stress, and immune responses involved in heat response. These miRNAs can be used as potential biomarkers for heat stress.


Assuntos
MicroRNA Circulante/genética , Resposta ao Choque Térmico/genética , Lactação/genética , Animais , Cruzamento , Bovinos , Doenças dos Bovinos/genética , Feminino , Perfilação da Expressão Gênica/métodos , Transtornos de Estresse por Calor/sangue , Temperatura Alta , MicroRNAs/genética , Leite/metabolismo , Gravidez , RNA Circular/genética , República da Coreia , Estações do Ano , Análise de Sequência de RNA/métodos
7.
PLoS One ; 15(8): e0237951, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32841302

RESUMO

High-throughput sequencing (HTS) has become increasingly popular as virus diagnostic tool. It has been used to detect and identify plant viruses and viroids in different types of matrices and tissues. A viral sequence enrichment method prior to HTS is required to increase the viral reads in the generated data to ease the bioinformatic analysis of generated sequences. In this study, we compared the sensitivity of three viral enrichment approaches, i.e. double stranded RNA (dsRNA), ribosomal RNA depleted total RNA (ribo-depleted totRNA) and small RNA (sRNA) for plant virus/viroid detection, followed by sequencing on MiSeq and NextSeq Illumina platforms. The three viral enrichment approaches used here enabled the detection of all viruses/viroid used in this study. When the data was normalised, the recovered viral/viroid nucleotides and depths were depending on the viral genome and the enrichment method used. Both dsRNA and ribo-depleted totRNA approaches detected a divergent strain of Wuhan aphid virus 2 that was not expected in this sample. Additionally, Vicia cryptic virus was detected in the data of dsRNA and sRNA approaches only. The results suggest that dsRNA enrichment has the highest potential to detect and identify plant viruses and viroids. The dsRNA approach used here detected all viruses/viroid, consumed less time, was lower in cost, and required less starting material. Therefore, this approach appears to be suitable for diagnostics laboratories.


Assuntos
Sequenciamento de Nucleotídeos em Larga Escala/métodos , Vírus de Plantas/genética , RNA Viral/genética , RNA Viral/isolamento & purificação , Análise de Sequência de RNA/métodos , Viroides/genética , Genômica
8.
PLoS Comput Biol ; 16(8): e1008120, 2020 08.
Artigo em Inglês | MEDLINE | ID: mdl-32804935

RESUMO

Complexity of cell-type composition has created much skepticism surrounding the interpretation of bulk tissue transcriptomic studies. Recent studies have shown that deconvolution algorithms can be applied to computationally estimate cell-type proportions from gene expression data of bulk blood samples, but their performance when applied to brain tissue is unclear. Here, we have generated an immunohistochemistry (IHC) dataset for five major cell-types from brain tissue of 70 individuals, who also have bulk cortical gene expression data. With the IHC data as the benchmark, this resource enables quantitative assessment of deconvolution algorithms for brain tissue. We apply existing deconvolution algorithms to brain tissue by using marker sets derived from human brain single cell and cell-sorted RNA-seq data. We show that these algorithms can indeed produce informative estimates of constituent cell-type proportions. In fact, neuronal subpopulations can also be estimated from bulk brain tissue samples. Further, we show that including the cell-type proportion estimates as confounding factors is important for reducing false associations between Alzheimer's disease phenotypes and gene expression. Lastly, we demonstrate that using more accurate marker sets can substantially improve statistical power in detecting cell-type specific expression quantitative trait loci (eQTLs).


Assuntos
Algoritmos , Encéfalo , Perfilação da Expressão Gênica/métodos , Análise de Sequência de RNA/métodos , Transcriptoma/genética , Encéfalo/citologia , Encéfalo/metabolismo , Biologia Computacional , Humanos , Imuno-Histoquímica , Especificidade de Órgãos/genética , Fenótipo , Locos de Características Quantitativas/genética , Análise de Célula Única
9.
Nat Commun ; 11(1): 4025, 2020 08 12.
Artigo em Inglês | MEDLINE | ID: mdl-32788667

RESUMO

Droplet-based high throughput single cell sequencing techniques tremendously advanced our insight into cell-to-cell heterogeneity. However, those approaches only allow analysis of one extremity of the transcript after short read sequencing. In consequence, information on splicing and sequence heterogeneity is lost. To overcome this limitation, several approaches that use long-read sequencing were introduced recently. Yet, those techniques are limited by low sequencing depth and/or lacking or inaccurate assignment of unique molecular identifiers (UMIs), which are critical for elimination of PCR bias and artifacts. We introduce ScNaUmi-seq, an approach that combines the high throughput of Oxford Nanopore sequencing with an accurate cell barcode and UMI assignment strategy. UMI guided error correction allows to generate high accuracy full length sequence information with the 10x Genomics single cell isolation system at high sequencing depths. We analyzed transcript isoform diversity in embryonic mouse brain and show that ScNaUmi-seq allows defining splicing and SNVs (RNA editing) at a single cell level.


Assuntos
Sequenciamento de Nucleotídeos em Larga Escala/métodos , Sequenciamento por Nanoporos , Nanoporos , Transcriptoma , Animais , Encéfalo , Expressão Gênica , Perfilação da Expressão Gênica , Genômica , Camundongos , Camundongos Endogâmicos C57BL , Isoformas de Proteínas , Receptores de AMPA/genética , Análise de Sequência de DNA/métodos , Análise de Sequência de RNA/métodos
10.
Nat Commun ; 11(1): 4175, 2020 08 21.
Artigo em Inglês | MEDLINE | ID: mdl-32826903

RESUMO

Somatic sensation is defined by the existence of a diversity of primary sensory neurons with unique biological features and response profiles to external and internal stimuli. However, there is no coherent picture about how this diversity of cell states is transcriptionally generated. Here, we use deep single cell analysis to resolve fate splits and molecular biasing processes during sensory neurogenesis in mice. Our results identify a complex series of successive and specific transcriptional changes in post-mitotic neurons that delineate hierarchical regulatory states leading to the generation of the main sensory neuron classes. In addition, our analysis identifies previously undetected early gene modules expressed long before fate determination although being clearly associated with defined sensory subtypes. Overall, the early diversity of sensory neurons is generated through successive bi-potential intermediates in which synchronization of relevant gene modules and concurrent repression of competing fate programs precede cell fate stabilization and final commitment.


Assuntos
Neurogênese/genética , Células Receptoras Sensoriais/citologia , Células Receptoras Sensoriais/fisiologia , Análise de Sequência de RNA/métodos , Análise de Célula Única/métodos , Animais , Diferenciação Celular , Subunidade alfa 3 de Fator de Ligação ao Core/genética , Modelos Animais de Doenças , Feminino , Regulação da Expressão Gênica no Desenvolvimento , Redes Reguladoras de Genes , Camundongos , Camundongos Endogâmicos C57BL , Camundongos Knockout , Neurônios/fisiologia , Células-Tronco
11.
PLoS Comput Biol ; 16(8): e1008133, 2020 08.
Artigo em Inglês | MEDLINE | ID: mdl-32833968

RESUMO

Breast cancer prognosis is challenging due to the heterogeneity of the disease. Various computational methods using bulk RNA-seq data have been proposed for breast cancer prognosis. However, these methods suffer from limited performances or ambiguous biological relevance, as a result of the neglect of intra-tumor heterogeneity. Recently, single cell RNA-sequencing (scRNA-seq) has emerged for studying tumor heterogeneity at cellular levels. In this paper, we propose a novel method, scPrognosis, to improve breast cancer prognosis with scRNA-seq data. scPrognosis uses the scRNA-seq data of the biological process Epithelial-to-Mesenchymal Transition (EMT). It firstly infers the EMT pseudotime and a dynamic gene co-expression network, then uses an integrative model to select genes important in EMT based on their expression variation and differentiation in different stages of EMT, and their roles in the dynamic gene co-expression network. To validate and apply the selected signatures to breast cancer prognosis, we use them as the features to build a prediction model with bulk RNA-seq data. The experimental results show that scPrognosis outperforms other benchmark breast cancer prognosis methods that use bulk RNA-seq data. Moreover, the dynamic changes in the expression of the selected signature genes in EMT may provide clues to the link between EMT and clinical outcomes of breast cancer. scPrognosis will also be useful when applied to scRNA-seq datasets of different biological processes other than EMT.


Assuntos
Neoplasias da Mama/patologia , Análise de Célula Única/métodos , Neoplasias da Mama/genética , Transição Epitelial-Mesenquimal , Feminino , Expressão Gênica , Humanos , Prognóstico , Análise de Sequência de RNA/métodos
12.
Gene ; 760: 145025, 2020 Nov 15.
Artigo em Inglês | MEDLINE | ID: mdl-32758582

RESUMO

Numerous cell lines for human alveolar rhabdomyosarcoma (ARMS) have been developed and are widely used to study biological processes of this myogenic cancer. The present study investigated the resemblance of commonly used ARMS cell lines to primary tumors in regards to gene expression. RNA-sequencing data was retrieved from published datasets for 4 commonly used ARMS cell lines and 35 ARMS primary tumors. The genes with most variable expression across primary tumors were used to calculate rank-based Spearman's correlation. The observed median correlations ranged from 0.36 to 0.61. RH-41 showed the highest median correlation while KYM-1 was the least correlated cell line. A significant number of genes dysregulated between tumors and non-tumors also exhibited similar expression patterns between tumors and cell lines, including The findings suggest that ARMS cell lines exhibit changes in gene expression compared to primary tumors and may not be completely representative of the disease process.


Assuntos
RNA Mensageiro/genética , Rabdomiossarcoma Alveolar/genética , Transcriptoma/genética , Linhagem Celular Tumoral , Bases de Dados Genéticas , Expressão Gênica/genética , Perfilação da Expressão Gênica/métodos , Regulação Neoplásica da Expressão Gênica/genética , Humanos , Modelos Biológicos , Rabdomiossarcoma Alveolar/metabolismo , Rabdomiossarcoma Alveolar/patologia , Rabdomiossarcoma Embrionário/genética , Rabdomiossarcoma Embrionário/metabolismo , Rabdomiossarcoma Embrionário/patologia , Análise de Sequência de RNA/métodos , Estatísticas não Paramétricas
13.
Nat Protoc ; 15(9): 2813-2836, 2020 09.
Artigo em Inglês | MEDLINE | ID: mdl-32747820

RESUMO

Several noncanonical initial nucleotides (NCINs) have been found to cap RNAs and possibly regulate RNA stability, transcription and translation. NAD+ is one of the NCINs that has recently been discovered to cap RNAs in a wide range of species. Identification of the NAD+-capped RNAs (NAD-RNAs) could help to unveil the cap-mediated regulation mechanisms. We previously reported a method termed NAD tagSeq for genome-wide analysis of NAD-RNAs. NAD tagSeq is based on the previously published NAD captureSeq protocol, which applies an enzymatic reaction and a click chemistry reaction to label NAD-RNAs with biotin followed by enrichment with streptavidin resin and identification by RNA sequencing. In the current NAD tagSeq method, NAD-RNAs are labeled with a synthetic RNA tag and identified by direct RNA sequencing based on Oxford Nanopore technology. Compared to NAD captureSeq, NAD tagSeq provides a simpler procedure for direct sequencing of NAD-RNAs and noncapped RNAs and affords information on the whole sequence organization of NAD-RNAs and the ratio of NAD-RNAs to total transcripts. Furthermore, NAD-RNAs can be enriched by hybridizing a complementary DNA probe to the RNA tag, thus increasing the sequencing coverage of NAD-RNAs. The strategy of tagging RNAs with a synthetic RNA tag and identifying them by direct RNA sequencing might be employed in analyzing other NCIN-capped RNAs. The experimental procedure of NAD tagSeq, including RNA extraction, RNA tagging and direct RNA sequencing, takes ~5 d, and initial data analysis can be completed within 2 d.


Assuntos
Perfilação da Expressão Gênica , NAD/metabolismo , Capuzes de RNA/genética , Capuzes de RNA/metabolismo , Análise de Sequência de RNA/métodos , Coloração e Rotulagem
14.
BMC Bioinformatics ; 21(1): 361, 2020 Aug 18.
Artigo em Inglês | MEDLINE | ID: mdl-32811424

RESUMO

BACKGROUND: Gene co-expression networks (GCNs) are powerful tools that enable biologists to examine associations between genes during different biological processes. With the advancement of new technologies, such as single-cell RNA sequencing (scRNA-seq), there is a need for developing novel network methods appropriate for new types of data. RESULTS: We present a novel sparse Bayesian factor model to explore the network structure associated with genes in scRNA-seq data. Latent factors impact the gene expression values for each cell and provide flexibility to account for common features of scRNA-seq: high proportions of zero values, increased cell-to-cell variability, and overdispersion due to abnormally large expression counts. From our model, we construct a GCN by analyzing the positive and negative associations of the factors that are shared between each pair of genes. CONCLUSIONS: Simulation studies demonstrate that our methodology has high power in identifying gene-gene associations while maintaining a nominal false discovery rate. In real data analyses, our model identifies more known and predicted protein-protein interactions than other competing network models.


Assuntos
Teorema de Bayes , Redes Reguladoras de Genes , Análise de Sequência de RNA/métodos , Bases de Dados Genéticas , Expressão Gênica , Análise de Célula Única
15.
BMC Bioinformatics ; 21(1): 375, 2020 Aug 28.
Artigo em Inglês | MEDLINE | ID: mdl-32859148

RESUMO

BACKGROUND: As the barriers to incorporating RNA sequencing (RNA-Seq) into biomedical studies continue to decrease, the complexity and size of RNA-Seq experiments are rapidly growing. Paired, longitudinal, and other correlated designs are becoming commonplace, and these studies offer immense potential for understanding how transcriptional changes within an individual over time differ depending on treatment or environmental conditions. While several methods have been proposed for dealing with repeated measures within RNA-Seq analyses, they are either restricted to handling only paired measurements, can only test for differences between two groups, and/or have issues with maintaining nominal false positive and false discovery rates. In this work, we propose a Bayesian hierarchical negative binomial generalized linear mixed model framework that can flexibly model RNA-Seq counts from studies with arbitrarily many repeated observations, can include covariates, and also maintains nominal false positive and false discovery rates in its posterior inference. RESULTS: In simulation studies, we showed that our proposed method (MCMSeq) best combines high statistical power (i.e. sensitivity or recall) with maintenance of nominal false positive and false discovery rates compared the other available strategies, especially at the smaller sample sizes investigated. This behavior was then replicated in an application to real RNA-Seq data where MCMSeq was able to find previously reported genes associated with tuberculosis infection in a cohort with longitudinal measurements. CONCLUSIONS: Failing to account for repeated measurements when analyzing RNA-Seq experiments can result in significantly inflated false positive and false discovery rates. Of the methods we investigated, whether they model RNA-Seq counts directly or worked on transformed values, the Bayesian hierarchical model implemented in the mcmseq R package (available at https://github.com/stop-pre16/mcmseq ) best combined sensitivity and nominal error rate control.


Assuntos
RNA/química , Análise de Sequência de RNA/métodos , Interface Usuário-Computador , Teorema de Bayes , Humanos , Método de Monte Carlo , RNA/genética , RNA/metabolismo , Tuberculose/genética , Tuberculose/patologia
16.
Emerg Infect Dis ; 26(10): 2401-2405, 2020 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-32610037

RESUMO

We describe validated protocols for generating high-quality, full-length severe acute respiratory syndrome coronavirus 2 genomes from primary samples. One protocol uses multiplex reverse transcription PCR, followed by MinION or MiSeq sequencing; the other uses singleplex, nested reverse transcription PCR and Sanger sequencing. These protocols enable sensitive virus sequencing in different laboratory environments.


Assuntos
Betacoronavirus/genética , Infecções por Coronavirus/virologia , Pneumonia Viral/virologia , RNA Viral/análise , Análise de Sequência de RNA/métodos , Sequenciamento Completo do Genoma/métodos , Reação em Cadeia da Polimerase Multiplex , Pandemias
17.
N Engl J Med ; 383(3): 218-228, 2020 07 16.
Artigo em Inglês | MEDLINE | ID: mdl-32668112

RESUMO

BACKGROUND: Rheumatoid arthritis, like many inflammatory diseases, is characterized by episodes of quiescence and exacerbation (flares). The molecular events leading to flares are unknown. METHODS: We established a clinical and technical protocol for repeated home collection of blood in patients with rheumatoid arthritis to allow for longitudinal RNA sequencing (RNA-seq). Specimens were obtained from 364 time points during eight flares over a period of 4 years in our index patient, as well as from 235 time points during flares in three additional patients. We identified transcripts that were differentially expressed before flares and compared these with data from synovial single-cell RNA-seq. Flow cytometry and sorted-blood-cell RNA-seq in additional patients were used to validate the findings. RESULTS: Consistent changes were observed in blood transcriptional profiles 1 to 2 weeks before a rheumatoid arthritis flare. B-cell activation was followed by expansion of circulating CD45-CD31-PDPN+ preinflammatory mesenchymal, or PRIME, cells in the blood from patients with rheumatoid arthritis; these cells shared features of inflammatory synovial fibroblasts. Levels of circulating PRIME cells decreased during flares in all 4 patients, and flow cytometry and sorted-cell RNA-seq confirmed the presence of PRIME cells in 19 additional patients with rheumatoid arthritis. CONCLUSIONS: Longitudinal genomic analysis of rheumatoid arthritis flares revealed PRIME cells in the blood during the period before a flare and suggested a model in which these cells become activated by B cells in the weeks before a flare and subsequently migrate out of the blood into the synovium. (Funded by the National Institutes of Health and others.).


Assuntos
Artrite Reumatoide/sangue , Linfócitos B/fisiologia , Expressão Gênica , Células-Tronco Mesenquimais , Análise de Sequência de RNA/métodos , Adulto , Artrite Reumatoide/genética , Artrite Reumatoide/imunologia , Feminino , Fibroblastos/metabolismo , Citometria de Fluxo , Humanos , Masculino , Células-Tronco Mesenquimais/metabolismo , Pessoa de Meia-Idade , Gravidade do Paciente , Inquéritos e Questionários , Exacerbação dos Sintomas , Líquido Sinovial/citologia
18.
Nucleic Acids Res ; 48(14): 7700-7711, 2020 08 20.
Artigo em Inglês | MEDLINE | ID: mdl-32652016

RESUMO

Arabidopsis thaliana transcriptomes have been extensively studied and characterized under different conditions. However, most of the current 'RNA-sequencing' technologies produce a relatively short read length and demand a reverse-transcription step, preventing effective characterization of transcriptome complexity. Here, we performed Direct RNA Sequencing (DRS) using the latest Oxford Nanopore Technology (ONT) with exceptional read length. We demonstrate that the complexity of the A. thaliana transcriptomes has been substantially under-estimated. The ONT direct RNA sequencing identified novel transcript isoforms at both the vegetative (14-day old seedlings, stage 1.04) and reproductive stages (stage 6.00-6.10) of development. Using in-house software called TrackCluster, we determined alternative transcription initiation (ATI), alternative polyadenylation (APA), alternative splicing (AS), and fusion transcripts. More than 38 500 novel transcript isoforms were identified, including six categories of fusion-transcripts that may result from differential RNA processing mechanisms. Aided by the Tombo algorithm, we found an enrichment of m5C modifications in the mobile mRNAs, consistent with a recent finding that m5C modification in mRNAs is crucial for their long-distance movement. In summary, ONT DRS offers an advantage in the identification and functional characterization of novel RNA isoforms and RNA base modifications, significantly improving annotation of the A. thaliana genome.


Assuntos
Arabidopsis/genética , Sequenciamento por Nanoporos/métodos , RNA de Plantas/química , RNA de Plantas/metabolismo , Análise de Sequência de RNA/métodos , Transcriptoma , Citosina/metabolismo , Metilação , Isoformas de RNA/química , Isoformas de RNA/metabolismo , RNA Mensageiro/química , RNA Mensageiro/metabolismo , RNA-Seq
19.
PLoS One ; 15(7): e0214497, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32639963

RESUMO

The Bashbay sheep (Ovis aries), an indigenous breed of Xinjiang, China, has many excellent characteristics. It is resistant to Mycoplasma ovipneumoniae infection, the causative agent of mycoplasma ovipneumonia, a chronic respiratory disease that is harmful to the sheep industry. To date, knowledge regarding the mechanisms responsible for M. ovipneumoniae pathogenesis in scant. Herein, we report the results of transcriptome profiling of lung tissues from Bashbay sheep experimentally infected with an M. ovipneumoniae strain at 4 and 14 days post-infection, in comparison to mock-infected animals (0 d). Transcriptome profiling was performed by deep RNA sequencing, using the Illumina platform. The analysis of differentially expressed genes was performed to determine concomitant gene-specific temporal patterns of mRNA expression in the lungs after M. ovipneumoniae infection. We found 1048 differentially expressed genes (575 up-regulated, 473 down-regulated) when comparing transcriptomic data at 4 and 0 days post-infection, and 2823 (1362 up-regulated, 1461 down-regulated) when comparing 14 versus 0 days post-infection. Kyoto Encyclopedia of Genes and Genomes pathway analysis showed that the differentially expressed genes at 4 and 14 versus 0 days post-infection were enriched in 245 and 287 pathways, respectively, and the Toll-like receptor (TLR) signaling pathway was considered most closely related to MO infection (p < 0.01). Two pathways (LAMP-TLR2/TLR6-MyD88-MKK6-AP1-IL1B and LAMP-TLR8MyD88-IRF5-RANTES) were identified based on the TLR signaling pathway from differentially expressed genes related M. ovipneumoniae infection. Gene Ontology analysis showed that differentially expressed genes in different groups were enriched for 1580 and 4561 terms, where those most closely related to M. ovipneumoniae infection are positive regulators of inflammatory responses (p < 0.01). These results could aid in understanding how M. ovipneumoniae infection progresses in the lungs and may provide useful information regarding key regulatory pathways.


Assuntos
Pulmão/metabolismo , Pneumonia por Mycoplasma/patologia , Análise de Sequência de RNA/métodos , Doenças dos Ovinos/patologia , Transcriptoma , Animais , Regulação para Baixo , Mycoplasma ovipneumoniae/isolamento & purificação , Mycoplasma ovipneumoniae/patogenicidade , Pneumonia por Mycoplasma/genética , Pneumonia por Mycoplasma/veterinária , RNA Mensageiro/química , RNA Mensageiro/metabolismo , Ovinos , Doenças dos Ovinos/genética , Doenças dos Ovinos/metabolismo , Transdução de Sinais/genética , Fatores de Tempo , Receptores Toll-Like/genética , Receptores Toll-Like/metabolismo , Regulação para Cima
20.
BMC Bioinformatics ; 21(1): 321, 2020 Jul 20.
Artigo em Inglês | MEDLINE | ID: mdl-32689929

RESUMO

BACKGROUND: Recent advancements in high-throughput sequencing technologies have generated an unprecedented amount of genomic data that must be stored, processed, and transmitted over the network for sharing. Lossy genomic data compression, especially of the base quality values of sequencing data, is emerging as an efficient way to handle this challenge due to its superior compression performance compared to lossless compression methods. Many lossy compression algorithms have been developed for and evaluated using DNA sequencing data. However, whether these algorithms can be used on RNA sequencing (RNA-seq) data remains unclear. RESULTS: In this study, we evaluated the impacts of lossy quality value compression on common RNA-seq data analysis pipelines including expression quantification, transcriptome assembly, and short variants detection using RNA-seq data from different species and sequencing platforms. Our study shows that lossy quality value compression could effectively improve RNA-seq data compression. In some cases, lossy algorithms achieved up to 1.2-3 times further reduction on the overall RNA-seq data size compared to existing lossless algorithms. However, lossy quality value compression could affect the results of some RNA-seq data processing pipelines, and hence its impacts to RNA-seq studies cannot be ignored in some cases. Pipelines using HISAT2 for alignment were most significantly affected by lossy quality value compression, while the effects of lossy compression on pipelines that do not depend on quality values, e.g., STAR-based expression quantification and transcriptome assembly pipelines, were not observed. Moreover, regardless of using either STAR or HISAT2 as the aligner, variant detection results were affected by lossy quality value compression, albeit to a lesser extent when STAR-based pipeline was used. Our results also show that the impacts of lossy quality value compression depend on the compression algorithms being used and the compression levels if the algorithm supports setting of multiple compression levels. CONCLUSIONS: Lossy quality value compression can be incorporated into existing RNA-seq analysis pipelines to alleviate the data storage and transmission burdens. However, care should be taken on the selection of compression tools and levels based on the requirements of the downstream analysis pipelines to avoid introducing undesirable adverse effects on the analysis results.


Assuntos
Algoritmos , Compressão de Dados/métodos , Compressão de Dados/normas , Genômica/métodos , Sequenciamento de Nucleotídeos em Larga Escala/métodos , Análise de Sequência de RNA/métodos , Sequência de Bases , Perfilação da Expressão Gênica , Genoma Humano , Humanos
SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA