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1.
Anticancer Res ; 41(9): 4609-4617, 2021 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-34475089

RESUMO

BACKGROUND/AIM: This study aimed to assess the yield of an Oncomine comprehensive assay v3 (OCAv3)-based next-generation sequencing (NGS) analysis for detecting anaplastic lymphoma kinase (ALK) and c-ros oncogene 1 (ROS1) fusions in non-small cell lung cancer (NSCLC). PATIENTS AND METHODS: NGS data from 85 NSCLC cases were reviewed. ALK and ROS1 fusion status was compared to conventional tests. RESULTS: ALK or ROS1 fusion reads were detected in 17 NSCLC cases. Results in 10 NSCLC cases showed concordance with conventional tests, high-count fusion reads, a lack of mutually exclusive mutations of ALK or ROS1, and frequent signet-ring cell component. Seven NSCLC cases showing discordant results exhibited low to intermediate fusion read counts and mutations mutually exclusive from ALK or ROS1. CONCLUSION: Cases showing high-count fusion reads in OCAv3-based NGS have a strong possibility of carrying ALK or ROS1 fusion. Cases with low- to intermediate-count fusion reads should be interpreted with caution and may require additional confirmative tests.


Assuntos
Quinase do Linfoma Anaplásico/genética , Carcinoma Pulmonar de Células não Pequenas/genética , Neoplasias Pulmonares/genética , Proteínas de Fusão Oncogênica/genética , Proteínas Tirosina Quinases/genética , Proteínas Proto-Oncogênicas/genética , Análise de Sequência de RNA/métodos , Adulto , Idoso , Idoso de 80 Anos ou mais , Análise Citogenética , Feminino , Sequenciamento de Nucleotídeos em Larga Escala , Humanos , Hibridização in Situ Fluorescente , Masculino , Pessoa de Meia-Idade , Mutação , Reação em Cadeia da Polimerase Via Transcriptase Reversa
2.
BMC Bioinformatics ; 22(Suppl 10): 419, 2021 Sep 03.
Artigo em Inglês | MEDLINE | ID: mdl-34479487

RESUMO

BACKGROUND: RNA velocity is a novel and powerful concept which enables the inference of dynamical cell state changes from seemingly static single-cell RNA sequencing (scRNA-seq) data. However, accurate estimation of RNA velocity is still a challenging problem, and the underlying kinetic mechanisms of transcriptional and splicing regulations are not fully clear. Moreover, scRNA-seq data tend to be sparse compared with possible cell states, and a given dataset of estimated RNA velocities needs imputation for some cell states not yet covered. RESULTS: We formulate RNA velocity prediction as a supervised learning problem of classification for the first time, where a cell state space is divided into equal-sized segments by directions as classes, and the estimated RNA velocity vectors are considered as ground truth. We propose Velo-Predictor, an ensemble learning pipeline for predicting RNA velocities from scRNA-seq data. We test different models on two real datasets, Velo-Predictor exhibits good performance, especially when XGBoost was used as the base predictor. Parameter analysis and visualization also show that the method is robust and able to make biologically meaningful predictions. CONCLUSION: The accurate result shows that Velo-Predictor can effectively simplify the procedure by learning a predictive model from gene expression data, which could help to construct a continous landscape and give biologists an intuitive picture about the trend of cellular dynamics.


Assuntos
RNA , Análise de Célula Única , Perfilação da Expressão Gênica , Aprendizado de Máquina , RNA/genética , Análise de Sequência de RNA , Sequenciamento Completo do Exoma
3.
Front Immunol ; 12: 677025, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34504487

RESUMO

The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is a global crisis; however, our current understanding of the host immune response to SARS-CoV-2 infection remains limited. Herein, we performed RNA sequencing using peripheral blood from acute and convalescent patients and interrogated the dynamic changes of adaptive immune response to SARS-CoV-2 infection over time. Our results revealed numerous alterations in these cohorts in terms of gene expression profiles and the features of immune repertoire. Moreover, a machine learning method was developed and resulted in the identification of five independent biomarkers and a collection of biomarkers that could accurately differentiate and predict the development of COVID-19. Interestingly, the increased expression of one of these biomarkers, UCHL1, a molecule related to nervous system damage, was associated with the clustering of severe symptoms. Importantly, analyses on immune repertoire metrics revealed the distinct kinetics of T-cell and B-cell responses to SARS-CoV-2 infection, with B-cell response plateaued in the acute phase and declined thereafter, whereas T-cell response can be maintained for up to 6 months post-infection onset and T-cell clonality was positively correlated with the serum level of anti-SARS-CoV-2 IgG. Together, the significantly altered genes or biomarkers, as well as the abnormally high levels of B-cell response in acute infection, may contribute to the pathogenesis of COVID-19 through mediating inflammation and immune responses, whereas prolonged T-cell response in the convalescents might help these patients in preventing reinfection. Thus, our findings could provide insight into the underlying molecular mechanism of host immune response to COVID-19 and facilitate the development of novel therapeutic strategies and effective vaccines.


Assuntos
COVID-19/genética , COVID-19/imunologia , Leucócitos Mononucleares/química , Transcriptoma , Adulto , Idoso , Anticorpos Antivirais/sangue , Linfócitos B/imunologia , Biomarcadores/sangue , COVID-19/sangue , COVID-19/virologia , China , Estudos de Coortes , Feminino , Humanos , Leucócitos Mononucleares/imunologia , Aprendizado de Máquina , Masculino , Pessoa de Meia-Idade , SARS-CoV-2/fisiologia , Análise de Sequência de RNA , Linfócitos T/imunologia , Ubiquitina Tiolesterase/genética , Ubiquitina Tiolesterase/imunologia
4.
BMC Genomics ; 22(1): 661, 2021 Sep 14.
Artigo em Inglês | MEDLINE | ID: mdl-34521337

RESUMO

BACKGROUND: Single-cell RNA sequencing (scRNA-seq) has quickly become one of the most dominant techniques in modern transcriptome assessment. In particular, 10X Genomics' Chromium system, with its high throughput approach, turn key and thorough user guide made this cutting-edge technique accessible to many laboratories using diverse animal models. However, standard pre-processing, including the alignment and cell filtering pipelines might not be ideal for every organism or tissue. Here we applied an alternative strategy, based on the pseudoaligner kallisto, on twenty-two publicly available single cell sequencing datasets from a wide range of tissues of eight organisms and compared the results with the standard 10X Genomics' Cell Ranger pipeline. RESULTS: In most of the tested samples, kallisto produced higher sequencing read alignment rates and total gene detection rates in comparison to Cell Ranger. Although datasets processed with Cell Ranger had higher cell counts, outside of human and mouse datasets, these additional cells were routinely of low quality, containing low gene detection rates. Thorough downstream analysis of one kallisto processed dataset, obtained from the zebrafish pineal gland, revealed clearer clustering, allowing the identification of an additional photoreceptor cell type that previously went undetected. The finding of the new cluster suggests that the photoreceptive pineal gland is essentially a bi-chromatic tissue containing both green and red cone-like photoreceptors and implies that the alignment and pre-processing pipeline can affect the discovery of biologically-relevant cell types. CONCLUSION: While Cell Ranger favors higher cell numbers, using kallisto results in datasets with higher median gene detection per cell. We could demonstrate that cell type identification was not hampered by the lower cell count, but in fact improved as a result of the high gene detection rate and the more stringent filtering. Depending on the acquired dataset, it can be beneficial to favor high quality cells and accept a lower cell count, leading to an improved classification of cell types.


Assuntos
RNA Citoplasmático Pequeno , Análise de Célula Única , Animais , Análise por Conglomerados , Perfilação da Expressão Gênica , Camundongos , Análise de Sequência de RNA , Software , Peixe-Zebra/genética
5.
Nat Commun ; 12(1): 5228, 2021 09 01.
Artigo em Inglês | MEDLINE | ID: mdl-34471111

RESUMO

EpiScanpy is a toolkit for the analysis of single-cell epigenomic data, namely single-cell DNA methylation and single-cell ATAC-seq data. To address the modality specific challenges from epigenomics data, epiScanpy quantifies the epigenome using multiple feature space constructions and builds a nearest neighbour graph using epigenomic distance between cells. EpiScanpy makes the many existing scRNA-seq workflows from scanpy available to large-scale single-cell data from other -omics modalities, including methods for common clustering, dimension reduction, cell type identification and trajectory learning techniques, as well as an atlas integration tool for scATAC-seq datasets. The toolkit also features numerous useful downstream functions, such as differential methylation and differential openness calling, mapping epigenomic features of interest to their nearest gene, or constructing gene activity matrices using chromatin openness. We successfully benchmark epiScanpy against other scATAC-seq analysis tools and show its outperformance at discriminating cell types.


Assuntos
Epigenômica/métodos , Análise de Célula Única/métodos , Cromatina , Sequenciamento de Cromatina por Imunoprecipitação , Análise por Conglomerados , Metilação de DNA , Humanos , Análise de Sequência de RNA
6.
Nat Commun ; 12(1): 4087, 2021 09 01.
Artigo em Inglês | MEDLINE | ID: mdl-34471112

RESUMO

We utilized forebrain organoids generated from induced pluripotent stem cells of patients with a syndromic form of Autism Spectrum Disorder (ASD) with a homozygous protein-truncating mutation in CNTNAP2, to study its effects on embryonic cortical development. Patients with this mutation present with clinical characteristics of brain overgrowth. Patient-derived forebrain organoids displayed an increase in volume and total cell number that is driven by increased neural progenitor proliferation. Single-cell RNA sequencing revealed PFC-excitatory neurons to be the key cell types expressing CNTNAP2. Gene ontology analysis of differentially expressed genes (DEgenes) corroborates aberrant cellular proliferation. Moreover, the DEgenes are enriched for ASD-associated genes. The cell-type-specific signature genes of the CNTNAP2-expressing neurons are associated with clinical phenotypes previously described in patients. The organoid overgrowth phenotypes were largely rescued after correction of the mutation using CRISPR-Cas9. This CNTNAP2-organoid model provides opportunity for further mechanistic inquiry and development of new therapeutic strategies for ASD.


Assuntos
Transtorno do Espectro Autista/metabolismo , Proteínas de Membrana/metabolismo , Proteínas do Tecido Nervoso/metabolismo , Organoides/metabolismo , Prosencéfalo/metabolismo , Adolescente , Transtorno do Espectro Autista/genética , Diferenciação Celular , Proliferação de Células , Criança , Feminino , Predisposição Genética para Doença/genética , Humanos , Células-Tronco Pluripotentes Induzidas , Proteínas de Membrana/genética , Mutação , Proteínas do Tecido Nervoso/genética , Neurônios/metabolismo , Fenótipo , Análise de Sequência de RNA
7.
Nat Commun ; 12(1): 5261, 2021 09 06.
Artigo em Inglês | MEDLINE | ID: mdl-34489404

RESUMO

The advent of single-cell RNA sequencing (scRNA-seq) technologies has revolutionized transcriptomic studies. However, large-scale integrative analysis of scRNA-seq data remains a challenge largely due to unwanted batch effects and the limited transferabilty, interpretability, and scalability of the existing computational methods. We present single-cell Embedded Topic Model (scETM). Our key contribution is the utilization of a transferable neural-network-based encoder while having an interpretable linear decoder via a matrix tri-factorization. In particular, scETM simultaneously learns an encoder network to infer cell type mixture and a set of highly interpretable gene embeddings, topic embeddings, and batch-effect linear intercepts from multiple scRNA-seq datasets. scETM is scalable to over 106 cells and confers remarkable cross-tissue and cross-species zero-shot transfer-learning performance. Using gene set enrichment analysis, we find that scETM-learned topics are enriched in biologically meaningful and disease-related pathways. Lastly, scETM enables the incorporation of known gene sets into the gene embeddings, thereby directly learning the associations between pathways and topics via the topic embeddings.


Assuntos
Bases de Dados Genéticas , Modelos Genéticos , Análise de Sequência de RNA/estatística & dados numéricos , Análise de Célula Única/métodos , Doença de Alzheimer/genética , Doença de Alzheimer/patologia , Animais , Transtorno Depressivo Maior/genética , Transtorno Depressivo Maior/patologia , Perfilação da Expressão Gênica/métodos , Perfilação da Expressão Gênica/estatística & dados numéricos , Genes Mitocondriais , Humanos , Camundongos , Redes Neurais de Computação , RNA Citoplasmático Pequeno , Retina/citologia , Retina/fisiologia , Análise de Sequência de RNA/métodos
8.
Nat Commun ; 12(1): 5256, 2021 09 06.
Artigo em Inglês | MEDLINE | ID: mdl-34489407

RESUMO

Tissue repair and healing remain among the most complicated processes that occur during postnatal life. Humans and other large organisms heal by forming fibrotic scar tissue with diminished function, while smaller organisms respond with scarless tissue regeneration and functional restoration. Well-established scaling principles reveal that organism size exponentially correlates with peak tissue forces during movement, and evolutionary responses have compensated by strengthening organ-level mechanical properties. How these adaptations may affect tissue injury has not been previously examined in large animals and humans. Here, we show that blocking mechanotransduction signaling through the focal adhesion kinase pathway in large animals significantly accelerates wound healing and enhances regeneration of skin with secondary structures such as hair follicles. In human cells, we demonstrate that mechanical forces shift fibroblasts toward pro-fibrotic phenotypes driven by ERK-YAP activation, leading to myofibroblast differentiation and excessive collagen production. Disruption of mechanical signaling specifically abrogates these responses and instead promotes regenerative fibroblast clusters characterized by AKT-EGR1.


Assuntos
Indóis/farmacologia , Mecanotransdução Celular/fisiologia , Pele/lesões , Sulfonamidas/farmacologia , Cicatrização/fisiologia , Animais , Diferenciação Celular , Células Cultivadas , Colágeno/metabolismo , Feminino , Fibroblastos , Quinase 1 de Adesão Focal/antagonistas & inibidores , Quinase 1 de Adesão Focal/metabolismo , Regeneração Tecidual Guiada , Humanos , Indóis/sangue , Mecanotransdução Celular/efeitos dos fármacos , Análise de Sequência de RNA , Análise de Célula Única , Pele/efeitos dos fármacos , Pele/patologia , Fenômenos Fisiológicos da Pele , Estresse Mecânico , Sulfonamidas/sangue , Suínos , Cicatrização/efeitos dos fármacos
9.
Nat Commun ; 12(1): 5262, 2021 09 06.
Artigo em Inglês | MEDLINE | ID: mdl-34489456

RESUMO

TFE3-translocation renal cell carcinoma (TFE3-tRCC) is a rare and heterogeneous subtype of kidney cancer with no standard treatment for advanced disease. We describe comprehensive molecular characteristics of 63 untreated primary TFE3-tRCCs based on whole-exome and RNA sequencing. TFE3-tRCC is highly heterogeneous, both clinicopathologically and genotypically. ASPSCR1-TFE3 fusion and several somatic copy number alterations, including the loss of 22q, are associated with aggressive features and poor outcomes. Apart from tumors with MED15-TFE3 fusion, most TFE3-tRCCs exhibit low PD-L1 expression and low T-cell infiltration. Unsupervised transcriptomic analysis reveals five molecular clusters with distinct angiogenesis, stroma, proliferation and KRAS down signatures, which show association with fusion patterns and prognosis. In line with the aggressive nature, the high angiogenesis/stroma/proliferation cluster exclusively consists of tumors with ASPSCR1-TFE3 fusion. Here, we describe the genomic and transcriptomic features of TFE3-tRCC and provide insights into precision medicine for this disease.


Assuntos
Fatores de Transcrição de Zíper de Leucina e Hélice-Alça-Hélix Básicos/genética , Carcinoma de Células Renais/genética , Carcinoma de Células Renais/mortalidade , Neoplasias Renais/genética , Neoplasias Renais/mortalidade , Adolescente , Adulto , Idoso , Carcinoma de Células Renais/patologia , Carcinoma de Células Renais/terapia , Criança , Pré-Escolar , Feminino , Regulação Neoplásica da Expressão Gênica , Fusão Gênica , Humanos , Peptídeos e Proteínas de Sinalização Intracelular/genética , Neoplasias Renais/patologia , Neoplasias Renais/terapia , Masculino , Pessoa de Meia-Idade , Mutação , Prognóstico , Análise de Sequência de RNA , Microambiente Tumoral/genética , Microambiente Tumoral/imunologia , Sequenciamento Completo do Exoma , Adulto Jovem
10.
Nat Commun ; 12(1): 5268, 2021 09 06.
Artigo em Inglês | MEDLINE | ID: mdl-34489460

RESUMO

Developmental steps in the trypanosome life-cycle involve transition between replicative and non-replicative forms specialised for survival in, and transmission between, mammalian and tsetse fly hosts. Here, using oligopeptide-induced differentiation in vitro, we model the progressive development of replicative 'slender' to transmissible 'stumpy' bloodstream form Trypanosoma brucei and capture the transcriptomes of 8,599 parasites using single cell transcriptomics (scRNA-seq). Using this framework, we detail the relative order of biological events during asynchronous development, profile dynamic gene expression patterns and identify putative regulators. We additionally map the cell cycle of proliferating parasites and position stumpy cell-cycle exit at early G1 before progression to a distinct G0 state. A null mutant for one transiently elevated developmental regulator, ZC3H20 is further analysed by scRNA-seq, identifying its point of failure in the developmental atlas. This approach provides a paradigm for the dissection of differentiation events in parasites, relevant to diverse transitions in pathogen biology.


Assuntos
Proteínas de Protozoários/genética , Trypanosoma brucei brucei/citologia , Trypanosoma brucei brucei/fisiologia , Animais , Ciclo Celular/genética , Ciclo Celular/fisiologia , Regulação da Expressão Gênica , Mutação , Percepção de Quorum , Análise de Sequência de RNA/métodos , Análise de Célula Única , Trypanosoma brucei brucei/genética
11.
BMC Plant Biol ; 21(1): 414, 2021 Sep 09.
Artigo em Inglês | MEDLINE | ID: mdl-34503445

RESUMO

BACKGROUND: Adventitious root formation is considered a major developmental step during the propagation of difficult to root plants, especially in horticultural crops. Recently, adventitious roots induced through plant tissue culture methods have also been used for production of phytochemicals such as flavonoids, anthocyanins and anthraquinones. It is rather well understood which horticultural species will easily form adventitious roots, but the factors affecting this process at molecular level or regulating the induction process in in vitro conditions are far less known. The present study was conducted to identify transcripts involved in in vitro induction and formation of adventitious roots using Arnebia euchroma leaves at different time points (intact leaf (control), 3 h, 12 h, 24 h, 3 d, 7 d, 10 d and 15 d). A. euchroma is an endangered medicinal Himalayan herb whose root contains red naphthoquinone pigments. These phytoconstituents are widely used as an herbal ingredient in Asian traditional medicine as well as natural colouring agent in food and cosmetics. RESULTS: A total of 137.93 to 293.76 million raw reads were generated and assembled to 54,587 transcripts with average length of 1512.27 bps and N50 of 2193 bps, respectively. In addition, 50,107 differentially expressed genes were identified and found to be involved in plant hormone signal transduction, cell wall modification and wound induced mitogen activated protein kinase signalling. The data exhibited dominance of auxin responsive (AUXIN RESPONSE FACTOR8, IAA13, GRETCHEN HAGEN3.1) and sucrose translocation (BETA-31 FRUCTOFURANOSIDASE and MONOSACCHARIDE-SENSING protein1) genes during induction phase. In the initiation phase, the expression of LATERAL ORGAN BOUNDARIES DOMAIN16, EXPANSIN-B15, ENDOGLUCANASE25 and LEUCINE-rich repeat EXTENSION-like proteins was increased. During the expression phase, the same transcripts, with exception of LATERAL ORGAN BOUNDARIES DOMAIN16 were identified. Overall, the transcriptomic analysis revealed a similar patterns of genes, however, their expression level varied in subsequent phases of in vitro adventitious root formation in A. euchroma. CONCLUSION: The results presented here will be helpful in understanding key regulators of in vitro adventitious root development in Arnebia species, which may be deployed in the future for phytochemical production at a commercial scale.


Assuntos
Boraginaceae/genética , Folhas de Planta , Proteínas de Plantas/genética , Raízes de Plantas/crescimento & desenvolvimento , Raízes de Plantas/genética , Boraginaceae/crescimento & desenvolvimento , Perfilação da Expressão Gênica , Regulação da Expressão Gênica de Plantas , Indóis/farmacologia , Anotação de Sequência Molecular , Folhas de Planta/efeitos dos fármacos , Folhas de Planta/genética , Plantas Medicinais/genética , Plantas Medicinais/crescimento & desenvolvimento , Análise de Sequência de RNA , Técnicas de Cultura de Tecidos/métodos
13.
Sci Rep ; 11(1): 17422, 2021 08 31.
Artigo em Inglês | MEDLINE | ID: mdl-34465838

RESUMO

The SARS-CoV-2 pandemic has raised concerns in the identification of the hosts of the virus since the early stages of the outbreak. To address this problem, we proposed a deep learning method, DeepHoF, based on extracting viral genomic features automatically, to predict the host likelihood scores on five host types, including plant, germ, invertebrate, non-human vertebrate and human, for novel viruses. DeepHoF made up for the lack of an accurate tool, reaching a satisfactory AUC of 0.975 in the five-classification, and could make a reliable prediction for the novel viruses without close neighbors in phylogeny. Additionally, to fill the gap in the efficient inference of host species for SARS-CoV-2 using existing tools, we conducted a deep analysis on the host likelihood profile calculated by DeepHoF. Using the isolates sequenced in the earliest stage of the COVID-19 pandemic, we inferred that minks, bats, dogs and cats were potential hosts of SARS-CoV-2, while minks might be one of the most noteworthy hosts. Several genes of SARS-CoV-2 demonstrated their significance in determining the host range. Furthermore, a large-scale genome analysis, based on DeepHoF's computation for the later pandemic in 2020, disclosed the uniformity of host range among SARS-CoV-2 samples and the strong association of SARS-CoV-2 between humans and minks.


Assuntos
COVID-19/virologia , Gatos/virologia , Quirópteros/virologia , Cães/virologia , Vison/virologia , SARS-CoV-2/classificação , Algoritmos , Animais , COVID-19/transmissão , Aprendizado Profundo , Especificidade de Hospedeiro , Humanos , RNA Viral/genética , SARS-CoV-2/genética , SARS-CoV-2/isolamento & purificação , Análise de Sequência de RNA
14.
J Transl Med ; 19(1): 388, 2021 09 10.
Artigo em Inglês | MEDLINE | ID: mdl-34507566

RESUMO

BACKGROUND: Acute myeloid leukemia (AML) is the most common acute leukemia in adults, with a median age of 68 in clinical diagnosis. About 60% patients are over 60 years old. There are various treatment options for AML patients. But for elderly patients, the complete remission rates are disappointing due to genetic, molecular, and age-related factors. Development of next-generation sequencing technologies makes it possible to seek individual strategies for patients in different ages. This study analyzed transcriptome profiles in platelets of AML patients in different ages for the first time. METHODS: Platelet RNA sequencing in AML of ten elderly and seven young patients were performed with Illumina TruSeq Stranded mRNA library Prep Kit and Illumina HiSeq4000 sequencing instrument. With the FASTQ sequencing data obtained, statistical analyses between elderly with young AML patients were analyzed by R program. GO and KEGG enrichment analyses were performed via R package clusterProfiler. TOP 10 down-regulated/up-regulated genes in elderly patients compared to young patients were selected with the threshold of |L2FC| > 2 and padj ≤ 0.0001. The down-regulated gene ATF4 was chosen by GSEA analysis and ROC analysis with AUC > 0.95. RESULTS: We found 3059 genes with differential transcript levels (GDTLs) in AML patients of different age. Among them, 2048 genes are down-regulated and 651 genes are up-regulated in elderly patients. We found that gene transcript profiles in elderly patients is obviously different from those in young patients, including a collection of down-regulated genes related to proteins processing in endoplasmic reticulum and immunity. We further identified that genes of pathway in cancer and mitogen activated protein kinase (MAPK) pathway, involved in natural immunity and metabolism, are significantly down-regulated in elderly patients. Among all screened genes with decreased transcript levels, we believe that activating transcription factor 4 (ATF4) is a biomarker indicating different chemotherapy strategies for elderly patients. CONCLUSIONS: In summary, gene transcript profiles are different in platelets of elderly and young AML patients. And ATF4 can be a useful biomarker indicating different chemotherapy strategies for AML patients with different ages.


Assuntos
Leucemia Mieloide Aguda , Transcriptoma , Adulto , Idoso , Plaquetas , Sequenciamento de Nucleotídeos em Larga Escala , Humanos , Leucemia Mieloide Aguda/tratamento farmacológico , Leucemia Mieloide Aguda/genética , Pessoa de Meia-Idade , Análise de Sequência de RNA , Transcriptoma/genética
15.
Int J Mol Sci ; 22(16)2021 Aug 19.
Artigo em Inglês | MEDLINE | ID: mdl-34445647

RESUMO

Unveiling the molecular features in the heart is essential for the study of heart diseases. Non-cardiomyocytes (nonCMs) play critical roles in providing structural and mechanical support to the working myocardium. There is an increasing amount of single-cell RNA-sequencing (scRNA-seq) data characterizing the transcriptomic profiles of nonCM cells. However, no tool allows researchers to easily access the information. Thus, in this study, we develop an open-access web portal, ExpressHeart, to visualize scRNA-seq data of nonCMs from five laboratories encompassing three species. ExpressHeart enables comprehensive visualization of major cell types and subtypes in each study; visualizes gene expression in each cell type/subtype in various ways; and facilitates identifying cell-type-specific and species-specific marker genes. ExpressHeart also provides an interface to directly combine information across datasets, for example, generating lists of high confidence DEGs by taking the intersection across different datasets. Moreover, ExpressHeart performs comparisons across datasets. We show that some homolog genes (e.g., Mmp14 in mice and mmp14b in zebrafish) are expressed in different cell types between mice and zebrafish, suggesting different functions across species. We expect ExpressHeart to serve as a valuable portal for investigators, shedding light on the roles of genes on heart development in nonCM cells.


Assuntos
Células Endoteliais/metabolismo , Fibroblastos/metabolismo , Ventrículos do Coração/metabolismo , Internet , Macrófagos/metabolismo , Pericitos/metabolismo , Transcriptoma , Algoritmos , Animais , Perfilação da Expressão Gênica , Humanos , Camundongos , Análise de Sequência de RNA , Análise de Célula Única , Software , Peixe-Zebra
16.
Int J Mol Sci ; 22(16)2021 Aug 13.
Artigo em Inglês | MEDLINE | ID: mdl-34445436

RESUMO

Apart from protein-coding Ribonucleic acids (RNAs), there exists a variety of non-coding RNAs (ncRNAs) which regulate complex cellular and molecular processes. High-throughput sequencing technologies and bioinformatics approaches have largely promoted the exploration of ncRNAs which revealed their crucial roles in gene regulation, miRNA binding, protein interactions, and splicing. Furthermore, ncRNAs are involved in the development of complicated diseases like cancer. Categorization of ncRNAs is essential to understand the mechanisms of diseases and to develop effective treatments. Sub-cellular localization information of ncRNAs demystifies diverse functionalities of ncRNAs. To date, several computational methodologies have been proposed to precisely identify the class as well as sub-cellular localization patterns of RNAs). This paper discusses different types of ncRNAs, reviews computational approaches proposed in the last 10 years to distinguish coding-RNA from ncRNA, to identify sub-types of ncRNAs such as piwi-associated RNA, micro RNA, long ncRNA, and circular RNA, and to determine sub-cellular localization of distinct ncRNAs and RNAs. Furthermore, it summarizes diverse ncRNA classification and sub-cellular localization determination datasets along with benchmark performance to aid the development and evaluation of novel computational methodologies. It identifies research gaps, heterogeneity, and challenges in the development of computational approaches for RNA sequence analysis. We consider that our expert analysis will assist Artificial Intelligence researchers with knowing state-of-the-art performance, model selection for various tasks on one platform, dominantly used sequence descriptors, neural architectures, and interpreting inter-species and intra-species performance deviation.


Assuntos
Biologia Computacional/métodos , RNA não Traduzido/classificação , RNA não Traduzido/metabolismo , Animais , Inteligência Artificial , Bases de Dados Factuais , Sequenciamento de Nucleotídeos em Larga Escala , Humanos , RNA não Traduzido/genética , Análise de Sequência de RNA , Distribuição Tecidual
17.
BMC Plant Biol ; 21(1): 366, 2021 Aug 11.
Artigo em Inglês | MEDLINE | ID: mdl-34380425

RESUMO

BACKGROUND: Small RNAs are short non-coding RNAs that are key gene regulators controlling various biological processes in eukaryotes. Plants may regulate discrete sets of sRNAs in response to pathogen attack. Sclerotinia sclerotiorum is an economically important pathogen affecting hundreds of plant species, including the economically important oilseed B. napus. However, there are limited studies on how regulation of sRNAs occurs in the S. sclerotiorum and B. napus pathosystem. RESULTS: We identified different classes of sRNAs from B. napus using high throughput sequencing of replicated mock and infected samples at 24 h post-inoculation (HPI). Overall, 3999 sRNA loci were highly expressed, of which 730 were significantly upregulated during infection. These 730 up-regulated sRNAs targeted 64 genes, including disease resistance proteins and transcriptional regulators. A total of 73 conserved miRNA families were identified in our dataset. Degradome sequencing identified 2124 cleaved mRNA products from these miRNAs from combined mock and infected samples. Among these, 50 genes were specific to infection. Altogether, 20 conserved miRNAs were differentially expressed and 8 transcripts were cleaved by the differentially expressed miRNAs miR159, miR5139, and miR390, suggesting they may have a role in the S. sclerotiorum response. A miR1885-triggered disease resistance gene-derived secondary sRNA locus was also identified and verified with degradome sequencing. We also found further evidence for silencing of a plant immunity related ethylene response factor gene by a novel sRNA using 5'-RACE and RT-qPCR. CONCLUSIONS: The findings in this study expand the framework for understanding the molecular mechanisms of the S. sclerotiorum and B. napus pathosystem at the sRNA level.


Assuntos
Ascomicetos/fisiologia , Brassica napus/genética , Brassica napus/microbiologia , Doenças das Plantas/microbiologia , RNA de Plantas , Pequeno RNA não Traduzido , Sequência Conservada , Resistência à Doença/genética , Regulação da Expressão Gênica de Plantas , Doenças das Plantas/genética , Análise de Sequência de RNA , Regulação para Cima
18.
Int J Mol Sci ; 22(16)2021 Aug 13.
Artigo em Inglês | MEDLINE | ID: mdl-34445398

RESUMO

Gibberellins (GAs) are an important group of phytohormones associated with diverse growth and developmental processes, including cell elongation, seed germination, and secondary growth. Recent genomic and genetic analyses have advanced our knowledge of GA signaling pathways and related genes in model plant species. However, functional genomics analyses of GA signaling pathways in Panax ginseng, a perennial herb, have rarely been carried out, despite its well-known economical and medicinal importance. Here, we conducted functional characterization of GA receptors and investigated their physiological roles in the secondary growth of P. ginseng storage roots. We found that the physiological and genetic functions of P. ginseng gibberellin-insensitive dwarf1s (PgGID1s) have been evolutionarily conserved. Additionally, the essential domains and residues in the primary protein structure for interaction with active GAs and DELLA proteins are well-conserved. Overexpression of PgGID1s in Arabidopsis completely restored the GA deficient phenotype of the Arabidopsis gid1a gid1c (atgid1a/c) double mutant. Exogenous GA treatment greatly enhanced the secondary growth of tap roots; however, paclobutrazol (PCZ), a GA biosynthetic inhibitor, reduced root growth in P. ginseng. Transcriptome profiling of P. ginseng roots revealed that GA-induced root secondary growth is closely associated with cell wall biogenesis, the cell cycle, the jasmonic acid (JA) response, and nitrate assimilation, suggesting that a transcriptional network regulate root secondary growth in P. ginseng. These results provide novel insights into the mechanism controlling secondary root growth in P. ginseng.


Assuntos
Perfilação da Expressão Gênica/métodos , Giberelinas/farmacologia , Panax/crescimento & desenvolvimento , Receptores de Superfície Celular/genética , Evolução Molecular , Regulação da Expressão Gênica no Desenvolvimento/efeitos dos fármacos , Regulação da Expressão Gênica de Plantas/efeitos dos fármacos , Mutação com Perda de Função , Panax/genética , Proteínas de Plantas/genética , Raízes de Plantas/genética , Raízes de Plantas/crescimento & desenvolvimento , Domínios Proteicos , Receptores de Superfície Celular/química , Análise de Sequência de RNA , Transdução de Sinais/efeitos dos fármacos , Triazóis/farmacologia
19.
Int J Mol Sci ; 22(16)2021 Aug 13.
Artigo em Inglês | MEDLINE | ID: mdl-34445418

RESUMO

Central pattern generators produce rhythmic behaviors independently of sensory input; however, their outputs can be modulated by neuropeptides, thereby allowing for functional flexibility. We investigated the effects of C-type allatostatins (AST-C) on the cardiac ganglion (CG), which is the central pattern generator that controls the heart of the American lobster, Homarus americanus, to identify the biological mechanism underlying the significant variability in individual responses to AST-C. We proposed that the presence of multiple receptors, and thus differential receptor distribution, was at least partly responsible for this observed variability. Using transcriptome mining and PCR-based cloning, we identified four AST-C receptors (ASTCRs) in the CG; we then characterized their cellular localization, binding potential, and functional activation. Only two of the four receptors, ASTCR1 and ASTCR2, were fully functional GPCRs that targeted to the cell surface and were activated by AST-C peptides in our insect cell expression system. All four, however, were amplified from CG cDNAs. Following the confirmation of ASTCR expression, we used physiological and bioinformatic techniques to correlate receptor expression with cardiac responses to AST-C across individuals. Expression of ASTCR1 in the CG showed a negative correlation with increasing contraction amplitude in response to AST-C perfusion through the lobster heart, suggesting that the differential expression of ASTCRs within the CG is partly responsible for the specific physiological response to AST-C exhibited by a given individual lobster.


Assuntos
Perfilação da Expressão Gênica/métodos , Nephropidae/genética , Neuropeptídeos/farmacologia , Receptores de Neuropeptídeos/genética , Receptores de Neuropeptídeos/metabolismo , Animais , Proteínas de Artrópodes/genética , Proteínas de Artrópodes/metabolismo , Sistema Cardiovascular/metabolismo , Membrana Celular/metabolismo , Clonagem Molecular , Mineração de Dados , Bases de Dados Genéticas , Regulação da Expressão Gênica/efeitos dos fármacos , Miocárdio/metabolismo , Nephropidae/efeitos dos fármacos , Nephropidae/metabolismo , Análise de Sequência de RNA , Células Sf9 , Distribuição Tecidual
20.
Int J Mol Sci ; 22(16)2021 Aug 13.
Artigo em Inglês | MEDLINE | ID: mdl-34445424

RESUMO

Biomarkers for predicting individual response to radiation and for dose verification are needed to improve radiotherapy. A biomarker should optimally show signal fidelity, meaning that its level is stable and proportional to the absorbed dose. miRNA levels in human blood serum were suggested as promising biomarkers. The aim of the present investigation was to test the miRNA biomarker in leukocytes of breast cancer patients undergoing external beam radiotherapy. Leukocytes were isolated from blood samples collected prior to exposure (control); on the day when a total dose of 2 Gy, 10 Gy, or 20 Gy was reached; and one month after therapy ended (46-50 Gy in total). RNA sequencing was performed and univariate analysis was used to analyse the effect of the radiation dose on the expression of single miRNAs. To check if combinations of miRNAs can predict absorbed dose, a multinomial logistic regression model was built using a training set from eight patients (representing 40 samples) and a validation set with samples from the remaining eight patients (15 samples). Finally, Broadside, an explorative interaction mining tool, was used to extract sets of interacting miRNAs. The most prominently increased miRNA was miR-744-5p, followed by miR-4461, miR-34a-5p, miR-6513-5p, miR-1246, and miR-454-3p. Decreased miRNAs were miR-3065-3p, miR-103a-2-5p, miR-30b-3p, and miR-5690. Generally, most miRNAs showed a relatively strong inter-individual variability and different temporal patterns over the course of radiotherapy. In conclusion, miR-744-5p shows promise as a stable miRNA marker, but most tested miRNAs displayed individual signal variability which, at least in this setting, may exclude them as sensitive biomarkers of radiation response.


Assuntos
Biomarcadores Tumorais/genética , Neoplasias da Mama/radioterapia , Perfilação da Expressão Gênica/métodos , Regulação Neoplásica da Expressão Gênica/efeitos da radiação , MicroRNAs/genética , Idoso , Biomarcadores Tumorais/sangue , Neoplasias da Mama/sangue , Neoplasias da Mama/genética , Fracionamento da Dose de Radiação , Feminino , Humanos , Pessoa de Meia-Idade , Análise de Sequência de RNA , Resultado do Tratamento , Regulação para Cima
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