Your browser doesn't support javascript.
Mostrar: 20 | 50 | 100
Resultados 1 - 20 de 4.957
Filtrar
1.
Recent Results Cancer Res ; 215: 89-104, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-31605225

RESUMO

Circulating tumor cells (CTCs) represent novel biomarkers, since they are obtainable through a simple and noninvasive blood draw or liquid biopsy. Here, we review the high-definition single-cell analysis (HD-SCA) workflow, which brings together modern methods of immunofluorescence with more sophisticated image processing to rapidly and accurately detect rare tumor cells among the milieu of platelets, erythrocytes, and leukocytes in the peripheral blood. In particular, we discuss progress in methods to measure CTC morphology and subcellular protein expression, and we highlight some initial applications that lead to fundamental new insights about the hematogenous phase of cancer, as well as its performance in early-stage diagnosis and treatment monitoring. We end with an outlook on how to further probe CTCs and the unique advantages of the HD-SCA workflow for improving the precision of cancer care.


Assuntos
Biologia Computacional , Neoplasias/patologia , Células Neoplásicas Circulantes/metabolismo , Biomarcadores Tumorais/análise , Biomarcadores Tumorais/genética , Ensaios de Triagem em Larga Escala , Humanos , Neoplasias/diagnóstico , Neoplasias/terapia , Células Neoplásicas Circulantes/patologia , Análise de Célula Única
2.
Rinsho Ketsueki ; 60(9): 1075-1083, 2019.
Artigo em Japonês | MEDLINE | ID: mdl-31597830

RESUMO

The mechanism underlying production of various types of blood cells from hematopoietic stem and progenitor cells has been a central theme in hematology. Conventionally, hematopoietic cell populations are analyzed by cell surface markers to judge cell types and differentiation stages, and by transplantation assays to assess differentiation potential. Recently, however, next-generation sequencing technology has enabled single-cell transcriptome and epigenome analyses and cell barcoding-based lineage tracing during unperturbed hematopoiesis. These innovative assays revealed that each cell population is extensively heterogenous. Many cells within hematopoietic stem cell populations may not be multipotent, and conversely, hematopoietic progenitor cells often display self-renewal capacity. Moreover, cells tend to make their lineage choice much earlier than previously thought. Altogether, these results challenge the current hierarchical differentiation models and propose new continuous models. Single-cell analyses are expected to greatly contribute to our understanding of normal and abnormal hematopoiesis and to the development of new therapies for blood disorders.


Assuntos
Hematopoese , Células-Tronco Hematopoéticas/citologia , Análise de Célula Única , Diferenciação Celular , Linhagem da Célula , Epigenômica , Humanos , Transcriptoma
3.
Chem Commun (Camb) ; 55(67): 9967-9970, 2019 Aug 15.
Artigo em Inglês | MEDLINE | ID: mdl-31367705

RESUMO

Herein, a seesaw ratiometric (SR) probe is designed which integrates fluorescence and surface enhanced Raman scattering (SERS) technology. Fluorescence imaging enables tracking of the spatiotemporal dynamic behaviour of telomerase. Meanwhile, SERS reverse ratiometric measurement can enable sensitive detection of telomerase activity in single living cells.


Assuntos
Corantes/química , Imagem Óptica/métodos , Análise de Célula Única/métodos , Análise Espectral Raman/métodos , Telomerase/metabolismo , DNA/química , Transferência Ressonante de Energia de Fluorescência/métodos , Ouro/química , Humanos , Células MCF-7 , Nanopartículas Metálicas/química
5.
Anticancer Res ; 39(8): 4011-4017, 2019 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-31366482

RESUMO

BACKGROUND/AIM: Genotoxicity is the capacity of an agent to induce damage to DNA. Given the close relationship between genotoxicity and carcinogenesis, several assays have been developed for detecting genetic damage. Among them, the single-cell gel (comet) assay plays an important role for evaluating DNA damage in mammalian cells, including those of the oral cavity. The purpose of this article was to provide a critical review of the application of single-cell gel comet assay to buccal cells. MATERIAL AND METHODS: A search of the scientific literature was conducted of published studies available on single-cell gel comet assay and oral cells. RESULTS: The results showed that the majority of studies were conducted on humans, whereas few were designed for use in rodents and in vitro. CONCLUSION: Further studies within the field are relevant for better understanding the underlying mechanisms of genotoxicity in oral cells, especially since the use of humans is quite complicated due to issues of ethics.


Assuntos
Carcinogênese/genética , Dano ao DNA/genética , Boca/efeitos dos fármacos , Análise de Célula Única/métodos , Ensaio Cometa/métodos , DNA/genética , Humanos , Boca/patologia , Mucosa Bucal/metabolismo , Mucosa Bucal/patologia , Mutagênicos
6.
Chem Commun (Camb) ; 55(70): 10404-10407, 2019 Aug 27.
Artigo em Inglês | MEDLINE | ID: mdl-31402361

RESUMO

We established an efficient method for single-cell miRNA analysis by droplet microfluidics, which has high sensitivity of single molecule detection and high throughput. Single-cell analysis of multiple miRNAs in various cells shows that miRNA expression is closely related to cancer type. CTC analysis shows that the method is applicable for rare cell analysis.


Assuntos
Sequenciamento de Nucleotídeos em Larga Escala/métodos , MicroRNAs/genética , Neoplasias/genética , Análise de Célula Única , Linhagem Celular Tumoral , Fluorescência , Humanos , Limite de Detecção
7.
Biol Res ; 52(1): 48, 2019 Aug 29.
Artigo em Inglês | MEDLINE | ID: mdl-31466525

RESUMO

BACKGROUND: Light exposure is a common stress factor in in vitro manipulation of embryos in the reproductive center. Many studies have shown the deleterious effects of high-intensity light exposure in different animal embryos. However, no transcriptomic studies have explored the light-induced injury and response in preimplantation embryos. RESULTS: Here, we adopt different time-courses and illumination intensities to treat mouse embryos at the 2-cell stage and evaluate their effects on blastulation. Meanwhile, single-cell transcriptomes from the 2-cell to blastocyst stage were analyzed after high-intensity light exposure. These data show that cells at each embryonic stage can be categorized into different light conditions. Further analyses of differentially expressed genes and GO terms revealed the light-induced injury as well as the potential repair response after high-intensity lighting. Maternal-to-zygote transition is also affected by the failure to remove maternal RNAs and deactivate zygotic genome expression. CONCLUSION: Our work revealed an integrated response to high-intensity lighting, involving morphological changes, long-lasting injury effects, and intracellular damage repair mechanisms.


Assuntos
Técnicas de Cultura Embrionária , Desenvolvimento Embrionário , Luz/efeitos adversos , Análise de Sequência de RNA , Análise de Célula Única , Animais , Blastocisto , Feminino , Camundongos , Camundongos Endogâmicos C57BL
8.
Cancer Discov ; 9(8): 1001-1002, 2019 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-31371323

RESUMO

Cancer-associated fibroblasts (CAF) have been implicated in diverse and sometimes divergent tumor modulatory processes that can be explained only by the existence of heterogeneous CAF subsets. In this issue of Cancer Discovery, Elyada and colleagues utilize single-cell transcriptomics to resolve CAF heterogeneity in pancreatic ductal adenocarcinoma and identify a novel antigen-presenting CAF population.See related article by Elyada et al., p. 1102.


Assuntos
Fibroblastos Associados a Câncer , Carcinoma Ductal Pancreático , Neoplasias Pancreáticas , Fibroblastos , Humanos , Análise de Célula Única
9.
Genome Biol ; 20(1): 155, 2019 08 06.
Artigo em Inglês | MEDLINE | ID: mdl-31387612

RESUMO

We describe a highly sensitive, quantitative, and inexpensive technique for targeted sequencing of transcript cohorts or genomic regions from thousands of bulk samples or single cells in parallel. Multiplexing is based on a simple method that produces extensive matrices of diverse DNA barcodes attached to invariant primer sets, which are all pre-selected and optimized in silico. By applying the matrices in a novel workflow named Barcode Assembly foR Targeted Sequencing (BART-Seq), we analyze developmental states of thousands of single human pluripotent stem cells, either in different maintenance media or upon Wnt/ß-catenin pathway activation, which identifies the mechanisms of differentiation induction. Moreover, we apply BART-Seq to the genetic screening of breast cancer patients and identify BRCA mutations with very high precision. The processing of thousands of samples and dynamic range measurements that outperform global transcriptomics techniques makes BART-Seq first targeted sequencing technique suitable for numerous research applications.


Assuntos
Perfilação da Expressão Gênica/métodos , Genômica/métodos , Sequenciamento de Nucleotídeos em Larga Escala/métodos , Análise de Sequência de RNA/métodos , Neoplasias da Mama/genética , Análise Custo-Benefício , Células-Tronco Embrionárias/metabolismo , Feminino , Perfilação da Expressão Gênica/economia , Genômica/economia , Sequenciamento de Nucleotídeos em Larga Escala/economia , Humanos , Células-Tronco Pluripotentes/metabolismo , Análise de Sequência de RNA/economia , Análise de Célula Única/economia , Análise de Célula Única/métodos , Via de Sinalização Wnt , Fluxo de Trabalho
10.
Genome Biol ; 20(1): 165, 2019 08 12.
Artigo em Inglês | MEDLINE | ID: mdl-31405383

RESUMO

To fully utilize the power of single-cell RNA sequencing (scRNA-seq) technologies for identifying cell lineages and bona fide transcriptional signals, it is necessary to combine data from multiple experiments. We present BERMUDA (Batch Effect ReMoval Using Deep Autoencoders), a novel transfer-learning-based method for batch effect correction in scRNA-seq data. BERMUDA effectively combines different batches of scRNA-seq data with vastly different cell population compositions and amplifies biological signals by transferring information among batches. We demonstrate that BERMUDA outperforms existing methods for removing batch effects and distinguishing cell types in multiple simulated and real scRNA-seq datasets.


Assuntos
Aprendizado Profundo , Perfilação da Expressão Gênica/métodos , Análise de Sequência de RNA/métodos , Algoritmos , Humanos , Leucócitos Mononucleares/metabolismo , Pâncreas/citologia , Pâncreas/metabolismo , Análise de Célula Única/métodos , Linfócitos T/metabolismo
11.
Nature ; 571(7764): 205-210, 2019 07.
Artigo em Inglês | MEDLINE | ID: mdl-31270459

RESUMO

The mammalian brain contains neurogenic niches that comprise neural stem cells and other cell types. Neurogenic niches become less functional with age, but how they change during ageing remains unclear. Here we perform single-cell RNA sequencing of young and old neurogenic niches in mice. The analysis of 14,685 single-cell transcriptomes reveals a decrease in activated neural stem cells, changes in endothelial cells and microglia, and an infiltration of T cells in old neurogenic niches. T cells in old brains are clonally expanded and are generally distinct from those in old blood, which suggests that they may experience specific antigens. T cells in old brains also express interferon-γ, and the subset of neural stem cells that has a high interferon response shows decreased proliferation in vivo. We find that T cells can inhibit the proliferation of neural stem cells in co-cultures and in vivo, in part by secreting interferon-γ. Our study reveals an interaction between T cells and neural stem cells in old brains, opening potential avenues through which to counteract age-related decline in brain function.


Assuntos
Envelhecimento/fisiologia , Encéfalo/citologia , Movimento Celular , Células-Tronco Neurais/citologia , Neurogênese , Análise de Célula Única , Nicho de Células-Tronco/fisiologia , Linfócitos T/citologia , Animais , Sangue , Proliferação de Células , Células Clonais/citologia , Técnicas de Cocultura , Células Endoteliais/citologia , Interferon gama/metabolismo , Masculino , Camundongos , Camundongos Endogâmicos C57BL , Microglia/citologia , Análise de Sequência de RNA , Transdução de Sinais , Linfócitos T/metabolismo , Transcriptoma/genética
12.
BMC Bioinformatics ; 20(1): 388, 2019 Jul 12.
Artigo em Inglês | MEDLINE | ID: mdl-31299886

RESUMO

BACKGROUND: Single-cell RNA-sequencing technologies provide a powerful tool for systematic dissection of cellular heterogeneity. However, the prevalence of dropout events imposes complications during data analysis and, despite numerous efforts from the community, this challenge has yet to be solved. RESULTS: Here we present a computational method, called RESCUE, to mitigate the dropout problem by imputing gene expression levels using information from other cells with similar patterns. Unlike existing methods, we use an ensemble-based approach to minimize the feature selection bias on imputation. By comparative analysis of simulated and real single-cell RNA-seq datasets, we show that RESCUE outperforms existing methods in terms of imputation accuracy which leads to more precise cell-type identification. CONCLUSIONS: Taken together, these results suggest that RESCUE is a useful tool for mitigating dropouts in single-cell RNA-seq data. RESCUE is implemented in R and available at https://github.com/seasamgo/rescue .


Assuntos
Análise de Sequência de RNA/métodos , Análise de Célula Única/métodos , Software , Viés , Células/metabolismo , Simulação por Computador , Regulação da Expressão Gênica , Humanos , RNA/genética , RNA/metabolismo
13.
J Phys Chem Lett ; 10(15): 4374-4381, 2019 Aug 01.
Artigo em Inglês | MEDLINE | ID: mdl-31313926

RESUMO

Voltage imaging allows mapping of the membrane potential in living cells. Yet, current intensity-based imaging approaches are limited to relative membrane potential changes, missing important information conveyed by the absolute value of the membrane voltage. This challenge arises from various factors affecting the signal intensity, such as concentration, illumination intensity, and photobleaching. Here, we demonstrate electronic preresonance hyperspectral stimulated Raman scattering (EPR-hSRS) for spectroscopic detection of the membrane voltage using a near-infrared-absorbing microbial rhodopsin expressed in E. coli. This newly developed near-infrared active microbial rhodopsin enables electronic preresonance SRS imaging at high sensitivity. By spectral profiling, we identified voltage-sensitive SRS peaks in the fingerprint region in single E. coli cells. These spectral signatures offer a new approach for quantitation of the absolute membrane voltage in living cells.


Assuntos
Rodopsinas Microbianas/química , Análise Espectral Raman/métodos , Escherichia coli/metabolismo , Concentração de Íons de Hidrogênio , Raios Infravermelhos , Potenciais da Membrana , Mutação , Rodopsinas Microbianas/genética , Rodopsinas Microbianas/metabolismo , Análise de Célula Única/métodos
14.
BMC Bioinformatics ; 20(1): 379, 2019 Jul 08.
Artigo em Inglês | MEDLINE | ID: mdl-31286861

RESUMO

BACKGROUND: Unsupervised machine learning methods (deep learning) have shown their usefulness with noisy single cell mRNA-sequencing data (scRNA-seq), where the models generalize well, despite the zero-inflation of the data. A class of neural networks, namely autoencoders, has been useful for denoising of single cell data, imputation of missing values and dimensionality reduction. RESULTS: Here, we present a striking feature with the potential to greatly increase the usability of autoencoders: With specialized training, the autoencoder is not only able to generalize over the data, but also to tease apart biologically meaningful modules, which we found encoded in the representation layer of the network. Our model can, from scRNA-seq data, delineate biological meaningful modules that govern a dataset, as well as give information as to which modules are active in each single cell. Importantly, most of these modules can be explained by known biological functions, as provided by the Hallmark gene sets. CONCLUSIONS: We discover that tailored training of an autoencoder makes it possible to deconvolute biological modules inherent in the data, without any assumptions. By comparisons with gene signatures of canonical pathways we see that the modules are directly interpretable. The scope of this discovery has important implications, as it makes it possible to outline the drivers behind a given effect of a cell. In comparison with other dimensionality reduction methods, or supervised models for classification, our approach has the benefit of both handling well the zero-inflated nature of scRNA-seq, and validating that the model captures relevant information, by establishing a link between input and decoded data. In perspective, our model in combination with clustering methods is able to provide information about which subtype a given single cell belongs to, as well as which biological functions determine that membership.


Assuntos
Perfilação da Expressão Gênica/métodos , Redes Neurais (Computação) , RNA Mensageiro/química , Análise de Sequência de RNA/métodos , Aprendizado de Máquina não Supervisionado , Análise por Conglomerados , RNA Mensageiro/metabolismo , Análise de Célula Única
15.
Nature ; 571(7765): 419-423, 2019 07.
Artigo em Inglês | MEDLINE | ID: mdl-31292545

RESUMO

Single-cell RNA sequencing (scRNA-seq) has highlighted the important role of intercellular heterogeneity in phenotype variability in both health and disease1. However, current scRNA-seq approaches provide only a snapshot of gene expression and convey little information on the true temporal dynamics and stochastic nature of transcription. A further key limitation of scRNA-seq analysis is that the RNA profile of each individual cell can be analysed only once. Here we introduce single-cell, thiol-(SH)-linked alkylation of RNA for metabolic labelling sequencing (scSLAM-seq), which integrates metabolic RNA labelling2, biochemical nucleoside conversion3 and scRNA-seq to record transcriptional activity directly by differentiating between new and old RNA for thousands of genes per single cell. We use scSLAM-seq to study the onset of infection with lytic cytomegalovirus in single mouse fibroblasts. The cell-cycle state and dose of infection deduced from old RNA enable dose-response analysis based on new RNA. scSLAM-seq thereby both visualizes and explains differences in transcriptional activity at the single-cell level. Furthermore, it depicts 'on-off' switches and transcriptional burst kinetics in host gene expression with extensive gene-specific differences that correlate with promoter-intrinsic features (TBP-TATA-box interactions and DNA methylation). Thus, gene-specific, and not cell-specific, features explain the heterogeneity in transcriptomes between individual cells and the transcriptional response to perturbations.


Assuntos
Regulação da Expressão Gênica/genética , Análise de Sequência de RNA/métodos , Análise de Célula Única , Transcrição Genética/genética , Alquilação , Animais , Ciclo Celular , Citomegalovirus/fisiologia , Metilação de DNA , Fibroblastos/metabolismo , Fibroblastos/virologia , Cinética , Camundongos , Regiões Promotoras Genéticas/genética , RNA/análise , RNA/química , Compostos de Sulfidrila/química
16.
Nature ; 571(7765): 349-354, 2019 07.
Artigo em Inglês | MEDLINE | ID: mdl-31292549

RESUMO

Ascidian embryos highlight the importance of cell lineages in animal development. As simple proto-vertebrates, they also provide insights into the evolutionary origins of cell types such as cranial placodes and neural crest cells. Here we have determined single-cell transcriptomes for more than 90,000 cells that span the entirety of development-from the onset of gastrulation to swimming tadpoles-in Ciona intestinalis. Owing to the small numbers of cells in ascidian embryos, this represents an average of over 12-fold coverage for every cell at every stage of development. We used single-cell transcriptome trajectories to construct virtual cell-lineage maps and provisional gene networks for 41 neural subtypes that comprise the larval nervous system. We summarize several applications of these datasets, including annotating the synaptome of swimming tadpoles and tracing the evolutionary origin of cell types such as the vertebrate telencephalon.


Assuntos
Linhagem da Célula/genética , Ciona intestinalis/citologia , Ciona intestinalis/genética , Análise de Célula Única , Transcriptoma , Animais , Sequência de Bases , Evolução Biológica , Ciona intestinalis/classificação , Ciona intestinalis/crescimento & desenvolvimento , Gastrulação , Redes Reguladoras de Genes , Larva/citologia , Larva/genética , Sistema Nervoso/citologia , Sistema Nervoso/metabolismo , Neurônios/citologia , Neurônios/metabolismo , Notocorda/citologia , Notocorda/embriologia , Especificidade de Órgãos , Sinapses/genética , Sinapses/metabolismo
17.
Nat Commun ; 10(1): 2907, 2019 07 02.
Artigo em Inglês | MEDLINE | ID: mdl-31266958

RESUMO

Single-nucleus RNA-seq (snRNA-seq) enables the interrogation of cellular states in complex tissues that are challenging to dissociate or are frozen, and opens the way to human genetics studies, clinical trials, and precise cell atlases of large organs. However, such applications are currently limited by batch effects, processing, and costs. Here, we present an approach for multiplexing snRNA-seq, using sample-barcoded antibodies to uniquely label nuclei from distinct samples. Comparing human brain cortex samples profiled with or without hashing antibodies, we demonstrate that nucleus hashing does not significantly alter recovered profiles. We develop DemuxEM, a computational tool that detects inter-sample multiplets and assigns singlets to their sample of origin, and validate its accuracy using sex-specific gene expression, species-mixing and natural genetic variation. Our approach will facilitate tissue atlases of isogenic model organisms or from multiple biopsies or longitudinal samples of one donor, and large-scale perturbation screens.


Assuntos
Anticorpos/análise , Núcleo Celular/genética , Genômica/métodos , Análise de Célula Única/métodos , Idoso , Idoso de 80 Anos ou mais , Animais , Núcleo Celular/química , Núcleo Celular/metabolismo , DNA/genética , Feminino , Humanos , Masculino , Camundongos , Camundongos Endogâmicos C57BL , Neurônios/química , Neurônios/citologia , Neurônios/metabolismo , Córtex Pré-Frontal/química , Córtex Pré-Frontal/metabolismo , RNA Mensageiro/genética , RNA Mensageiro/metabolismo
18.
BMC Bioinformatics ; 20(1): 369, 2019 Jul 01.
Artigo em Inglês | MEDLINE | ID: mdl-31262249

RESUMO

BACKGROUND: Single cell RNA sequencing (scRNA-seq) brings unprecedented opportunities for mapping the heterogeneity of complex cellular environments such as bone marrow, and provides insight into many cellular processes. Single cell RNA-seq has a far larger fraction of missing data reported as zeros (dropouts) than traditional bulk RNA-seq, and unsupervised clustering combined with Principal Component Analysis (PCA) can be used to overcome this limitation. After clustering, however, one has to interpret the average expression of markers on each cluster to identify the corresponding cell types, and this is normally done by hand by an expert curator. RESULTS: We present a computational tool for processing single cell RNA-seq data that uses a voting algorithm to automatically identify cells based on approval votes received by known molecular markers. Using a stochastic procedure that accounts for imbalances in the number of known molecular signatures for different cell types, the method computes the statistical significance of the final approval score and automatically assigns a cell type to clusters without an expert curator. We demonstrate the utility of the tool in the analysis of eight samples of bone marrow from the Human Cell Atlas. The tool provides a systematic identification of cell types in bone marrow based on a list of markers of immune cell types, and incorporates a suite of visualization tools that can be overlaid on a t-SNE representation. The software is freely available as a Python package at https://github.com/sdomanskyi/DigitalCellSorter . CONCLUSIONS: This methodology assures that extensive marker to cell type matching information is taken into account in a systematic way when assigning cell clusters to cell types. Moreover, the method allows for a high throughput processing of multiple scRNA-seq datasets, since it does not involve an expert curator, and it can be applied recursively to obtain cell sub-types. The software is designed to allow the user to substitute the marker to cell type matching information and apply the methodology to different cellular environments.


Assuntos
Células da Medula Óssea/citologia , Perfilação da Expressão Gênica/métodos , Análise de Sequência de RNA/métodos , Software , Algoritmos , Células da Medula Óssea/metabolismo , Análise por Conglomerados , Humanos , Análise de Componente Principal , Análise de Célula Única
19.
Nature ; 571(7765): 355-360, 2019 07.
Artigo em Inglês | MEDLINE | ID: mdl-31270458

RESUMO

Defining the transcriptomic identity of malignant cells is challenging in the absence of surface markers that distinguish cancer clones from one another, or from admixed non-neoplastic cells. To address this challenge, here we developed Genotyping of Transcriptomes (GoT), a method to integrate genotyping with high-throughput droplet-based single-cell RNA sequencing. We apply GoT to profile 38,290 CD34+ cells from patients with CALR-mutated myeloproliferative neoplasms to study how somatic mutations corrupt the complex process of human haematopoiesis. High-resolution mapping of malignant versus normal haematopoietic progenitors revealed an increasing fitness advantage with myeloid differentiation of cells with mutated CALR. We identified the unfolded protein response as a predominant outcome of CALR mutations, with a considerable dependency on cell identity, as well as upregulation of the NF-κB pathway specifically in uncommitted stem cells. We further extended the GoT toolkit to genotype multiple targets and loci that are distant from transcript ends. Together, these findings reveal that the transcriptional output of somatic mutations in myeloproliferative neoplasms is dependent on the native cell identity.


Assuntos
Genótipo , Mutação , Transtornos Mieloproliferativos/genética , Transtornos Mieloproliferativos/patologia , Neoplasias/genética , Neoplasias/patologia , Transcriptoma/genética , Animais , Antígenos CD34/metabolismo , Calreticulina/genética , Linhagem Celular , Proliferação de Células , Células Clonais/classificação , Células Clonais/metabolismo , Células Clonais/patologia , Endorribonucleases/metabolismo , Hematopoese/genética , Células-Tronco Hematopoéticas/classificação , Células-Tronco Hematopoéticas/metabolismo , Células-Tronco Hematopoéticas/patologia , Sequenciamento de Nucleotídeos em Larga Escala/métodos , Humanos , Camundongos , Modelos Moleculares , Transtornos Mieloproliferativos/classificação , NF-kappa B/metabolismo , Neoplasias/classificação , Células-Tronco Neoplásicas/citologia , Células-Tronco Neoplásicas/metabolismo , Células-Tronco Neoplásicas/patologia , Mielofibrose Primária/genética , Mielofibrose Primária/patologia , Proteínas Serina-Treonina Quinases/metabolismo , Análise de Sequência de RNA/métodos , Análise de Célula Única/métodos , Resposta a Proteínas não Dobradas/genética
20.
Nat Commun ; 10(1): 2975, 2019 07 05.
Artigo em Inglês | MEDLINE | ID: mdl-31278265

RESUMO

The rapid development of single-cell transcriptomic technologies has helped uncover the cellular heterogeneity within cell populations. However, bulk RNA-seq continues to be the main workhorse for quantifying gene expression levels due to technical simplicity and low cost. To most effectively extract information from bulk data given the new knowledge gained from single-cell methods, we have developed a novel algorithm to estimate the cell-type composition of bulk data from a single-cell RNA-seq-derived cell-type signature. Comparison with existing methods using various real RNA-seq data sets indicates that our new approach is more accurate and comprehensive than previous methods, especially for the estimation of rare cell types. More importantly, our method can detect cell-type composition changes in response to external perturbations, thereby providing a valuable, cost-effective method for dissecting the cell-type-specific effects of drug treatments or condition changes. As such, our method is applicable to a wide range of biological and clinical investigations.


Assuntos
Perfilação da Expressão Gênica/métodos , Análise de Sequência de RNA/métodos , Análise de Célula Única/métodos , Algoritmos , Conjuntos de Dados como Assunto , Estudos de Viabilidade , Feminino , Sequenciamento de Nucleotídeos em Larga Escala/métodos , Humanos , Análise dos Mínimos Quadrados , Melanoma/genética , Neoplasias Ovarianas/genética , Neoplasias Cutâneas/genética , Transcriptoma/genética
SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA