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1.
BMC Ecol Evol ; 21(1): 19, 2021 Feb 09.
Artigo em Inglês | MEDLINE | ID: mdl-33563214

RESUMO

BACKGROUND: Rearrangement is an important topic in the research of amphibian mitochondrial genomes ("mitogenomes" hereafter), whose causes and mechanisms remain enigmatic. Globally examining mitogenome rearrangements and uncovering their characteristics can contribute to a better understanding of mitogenome evolution. RESULTS: Here we systematically investigated mitogenome arrangements of 232 amphibians including four newly sequenced Dicroglossidae mitogenomes. The results showed that our new sequenced mitogenomes all possessed a trnM tandem duplication, which was not exclusive to Dicroglossidae. By merging the same arrangements, the mitogenomes of ~ 80% species belonged to the four major patterns, the major two of which were typical vertebrate arrangement and typical neobatrachian arrangement. Using qMGR for calculating rearrangement frequency (RF) (%), we found that the control region (CR) (RF = 45.04) and trnL2 (RF = 38.79) were the two most frequently rearranged components. Forty-seven point eight percentage of amphibians possessed rearranged mitogenomes including all neobatrachians and their distribution was significantly clustered in the phylogenetic trees (p < 0.001). In addition, we argued that the typical neobatrachian arrangement may have appeared in the Late Jurassic according to possible occurrence time estimation. CONCLUSION: It was the first global census of amphibian mitogenome arrangements from the perspective of quantity statistics, which helped us to systematically understand the type, distribution, frequency and phylogenetic characteristics of these rearrangements.

2.
Nat Commun ; 12(1): 652, 2021 01 28.
Artigo em Inglês | MEDLINE | ID: mdl-33510160

RESUMO

Injury and loss of oligodendrocytes can cause demyelinating diseases such as multiple sclerosis. To improve our understanding of human oligodendrocyte development, which could facilitate development of remyelination-based treatment strategies, here we describe time-course single-cell-transcriptomic analysis of developing human stem cell-derived oligodendrocyte-lineage-cells (hOLLCs). The study includes hOLLCs derived from both genome engineered embryonic stem cell (ESC) reporter cells containing an Identification-and-Purification tag driven by the endogenous PDGFRα promoter and from unmodified induced pluripotent (iPS) cells. Our analysis uncovers substantial transcriptional heterogeneity of PDGFRα-lineage hOLLCs. We discover sub-populations of human oligodendrocyte progenitor cells (hOPCs) including a potential cytokine-responsive hOPC subset, and identify candidate regulatory genes/networks that define the identity of these sub-populations. Pseudotime trajectory analysis defines developmental pathways of oligodendrocytes vs astrocytes from PDGFRα-expressing hOPCs and predicts differentially expressed genes between the two lineages. In addition, pathway enrichment analysis followed by pharmacological intervention of these pathways confirm that mTOR and cholesterol biosynthesis signaling pathways are involved in maturation of oligodendrocytes from hOPCs.


Assuntos
Heterogeneidade Genética , Variação Genética , Células-Tronco Pluripotentes Induzidas/metabolismo , Células Precursoras de Oligodendrócitos/metabolismo , Análise de Célula Única/métodos , Transcriptoma/genética , Astrócitos/citologia , Astrócitos/metabolismo , Diferenciação Celular/genética , Linhagem Celular , Linhagem da Célula/genética , Colesterol/biossíntese , Células-Tronco Embrionárias/citologia , Células-Tronco Embrionárias/metabolismo , Redes Reguladoras de Genes/genética , Humanos , Células-Tronco Pluripotentes Induzidas/citologia , Células Precursoras de Oligodendrócitos/citologia , Receptor alfa de Fator de Crescimento Derivado de Plaquetas/genética , Receptor alfa de Fator de Crescimento Derivado de Plaquetas/metabolismo , Transdução de Sinais/genética , Serina-Treonina Quinases TOR/genética , Serina-Treonina Quinases TOR/metabolismo
3.
Artigo em Inglês | MEDLINE | ID: mdl-33513105

RESUMO

The inference of Boolean networks is crucial for analyzing the topology and dynamics of gene regulatory networks. Many data-driven approaches using evolutionary algorithms have been proposed based on time-series data. However, the ability to infer both network topology and dynamics is restricted by their inflexible encoding schemes. To address this problem, we propose a novel Boolean network inference algorithm for inferring both network topology and dynamics simultaneously. The main idea is that, we use a marker-based genetic algorithm to encode both regulatory nodes and logical operators in a chromosome. By using the markers and introducing more logical operators, the proposed algorithm can infer more diverse candidate Boolean functions. The proposed algorithm is applied to five networks, including two artificial Boolean networks and three real-world gene regulatory networks. Compared with other algorithms, the experimental results demonstrate that our proposed algorithm infers more accurate topology and dynamics.

4.
Environ Technol ; : 1-14, 2020 Nov 26.
Artigo em Inglês | MEDLINE | ID: mdl-33136522

RESUMO

The preparation method of PVDF/SiO2-g-CDs blended membrane was that the silanized modified carbon dots (CDs) were grafted onto the PVDF/SiO2 blended membrane surface. The surface composition, morphology, hydrophilicity, fluorescence performance and metal ions adsorption performance of PVDF/SiO2-g-CDs blended membrane were studied. The fluorescence quenching effect of the membrane with Hg2+ and Fe3+ was obvious. The quenching mechanism was the complexation of metal ions with the functional groups of CDs including -NH2, -OH and -COOH. The optical detection limits of PVDF/SiO2-g-CDs blended membrane for Hg2+ was 1.6 nM in the linear range of 0.0025-20 µM, and the optical detection limits for Fe3+ was 2.1 µM in the linear range of 0.5-5000 µM. The maximum adsorption capacity of PVDF/SiO2-g-CDs blended membrane for Fe3+ was 47.04 mg·g-1. The adsorption of the membrane conformed to the pseudo-second-order kinetics and Langumir model, and belonged to monolayer chemical adsorption on the membrane surface. Through adsorption thermodynamic analysis, adsorption was a spontaneous endothermic process. The recovery rate of fluorescence and adsorption capacity could still be maintained above 82% after five cycles. The PVDF/SiO2-g-CDs blended membrane had the ability to regenerate. In summary, the PVDF/SiO2-g-CDs blended membrane had the dual functions of detecting and adsorbing metal ions, and had broad application prospects in sewage treatment.

5.
JCI Insight ; 5(20)2020 Oct 15.
Artigo em Inglês | MEDLINE | ID: mdl-32970632

RESUMO

Myeloid cells are increasingly recognized as major players in transplant rejection. Here, we used a murine kidney transplantation model and single cell transcriptomics to dissect the contribution of myeloid cell subsets and their potential signaling pathways to kidney transplant rejection. Using a variety of bioinformatic techniques, including machine learning, we demonstrate that kidney allograft-infiltrating myeloid cells followed a trajectory of differentiation from monocytes to proinflammatory macrophages, and they exhibited distinct interactions with kidney allograft parenchymal cells. While this process correlated with a unique pattern of myeloid cell transcripts, a top gene identified was Axl, a member of the receptor tyrosine kinase family Tyro3/Axl/Mertk (TAM). Using kidney transplant recipients with Axl gene deficiency, we further demonstrate that Axl augmented intragraft differentiation of proinflammatory macrophages, likely via its effect on the transcription factor Cebpb. This, in turn, promoted intragraft recruitment, differentiation, and proliferation of donor-specific T cells, and it enhanced early allograft inflammation evidenced by histology. We conclude that myeloid cell Axl expression identified by single cell transcriptomics of kidney allografts in our study plays a major role in promoting intragraft myeloid cell and T cell differentiation, and it presents a potentially novel therapeutic target for controlling kidney allograft rejection and improving kidney allograft survival.

6.
Genome Biol ; 21(1): 218, 2020 08 27.
Artigo em Inglês | MEDLINE | ID: mdl-32854757

RESUMO

BACKGROUND: The rapid development of single-cell RNA-sequencing (scRNA-seq) technologies has led to the emergence of many methods for removing systematic technical noises, including imputation methods, which aim to address the increased sparsity observed in single-cell data. Although many imputation methods have been developed, there is no consensus on how methods compare to each other. RESULTS: Here, we perform a systematic evaluation of 18 scRNA-seq imputation methods to assess their accuracy and usability. We benchmark these methods in terms of the similarity between imputed cell profiles and bulk samples and whether these methods recover relevant biological signals or introduce spurious noise in downstream differential expression, unsupervised clustering, and pseudotemporal trajectory analyses, as well as their computational run time, memory usage, and scalability. Methods are evaluated using data from both cell lines and tissues and from both plate- and droplet-based single-cell platforms. CONCLUSIONS: We found that the majority of scRNA-seq imputation methods outperformed no imputation in recovering gene expression observed in bulk RNA-seq. However, the majority of the methods did not improve performance in downstream analyses compared to no imputation, in particular for clustering and trajectory analysis, and thus should be used with caution. In addition, we found substantial variability in the performance of the methods within each evaluation aspect. Overall, MAGIC, kNN-smoothing, and SAVER were found to outperform the other methods most consistently.

7.
Genome Biol ; 21(1): 161, 2020 07 03.
Artigo em Inglês | MEDLINE | ID: mdl-32620137

RESUMO

Single-cell sequencing assay for transposase-accessible chromatin (scATAC-seq) is the state-of-the-art technology for analyzing genome-wide regulatory landscapes in single cells. Single-cell ATAC-seq data are sparse and noisy, and analyzing such data is challenging. Existing computational methods cannot accurately reconstruct activities of individual cis-regulatory elements (CREs) in individual cells or rare cell subpopulations. We present a new statistical framework, SCATE, that adaptively integrates information from co-activated CREs, similar cells, and publicly available regulome data to substantially increase the accuracy for estimating activities of individual CREs. We demonstrate that SCATE can be used to better reconstruct the regulatory landscape of a heterogeneous sample.

8.
Evol Comput ; : 1-31, 2020 May 06.
Artigo em Inglês | MEDLINE | ID: mdl-32375006

RESUMO

Dynamic Flexible Job Shop Scheduling (DFJSS) is an important and challenging problem, and can have multiple conflicting objectives. Genetic Programming Hyper-Heuristic (GPHH) is a promising approach to fast respond to the dynamic and unpredictable events in DFJSS. A GPHH algorithm evolves dispatching rules (DRs) that are used to make decisions during the scheduling process (i.e., the so-called heuristic template). In DFJSS, there are two kinds of scheduling decisions: the routing decision that allocates each operation to a machine to process it, and the sequencing decision that selects the next job to be processed by each idle machine. The traditional heuristic template makes both routing and sequencing decisions in a non-delay manner, which may have limitations in handling the dynamic environment. In this article, we propose a novel heuristic template that delays the routing decisions rather than making them immediately. This way, all the decisions can be made under the latest and most accurate information. We propose three different delayed routing strategies, and automatically evolve the rules in the heuristic template by GPHH. We evaluate the newly proposed GPHH with Delayed Routing (GPHH-DR) on a multiobjective DFJSS that optimises the energy efficiency and mean tardiness. The experimental results show that GPHH-DR significantly outperformed the state-of-the-art GPHH methods. We further demonstrated the efficacy of the proposed heuristic template with delayed routing, which suggests the importance of delaying the routing decisions.

9.
Genes (Basel) ; 11(3)2020 02 26.
Artigo em Inglês | MEDLINE | ID: mdl-32111006

RESUMO

Prognostic gene signatures are critical in cancer prognosis assessments and their pinpoint treatments. However, their network properties remain unclear. Here, we obtained nine prognostic gene sets including 1439 prognostic genes of different cancers from related publications. Four network centralities were used to examine the network properties of prognostic genes (PG) compared with other gene sets based on the Human Protein Reference Database (HPRD) and String networks. We also proposed three novel network measures for further investigating the network properties of prognostic gene sets (PGS) besides clustering coefficient. The results showed that PG did not occupy key positions in the human protein interaction network and were more similar to essential genes rather than cancer genes. However, PGS had significantly smaller intra-set distance (IAD) and inter-set distance (IED) in comparison with random sets (p-value < 0.001). Moreover, we also found that PGS tended to be distributed within network modules rather than between modules (p-value < 0.01), and the functional intersection of the modules enriched with PGS was closely related to cancer development and progression. Our research reveals the common network properties of cancer prognostic gene signatures in the human protein interactome. We argue that these are biologically meaningful and useful for understanding their molecular mechanism.

10.
ISA Trans ; 104: 44-52, 2020 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-31924313

RESUMO

Industrial cyber-physical systems (ICPSs) have received increasing attention from both academia and industry. However, the privacy-utility trade-off of process parameters is still a challenge in the ICPSs. To address this challenge, a Kalman filter-based differential privacy and an unscented Kalman filter-based differential privacy algorithms are derived. In order to increase the utility of process parameters while protecting the privacy of process parameters, a differentially private square root unscented Kalman filter algorithm is proposed by employing the square root unscented Kalman filter and differential privacy. The experiments based on a numerical control lathe are presented to prove the privacy and evaluate the utility of process parameters.

11.
Elife ; 92020 Jan 28.
Artigo em Inglês | MEDLINE | ID: mdl-31989924

RESUMO

Transcriptional repression needs to be rapidly reversible during embryonic development. This extends to the Hedgehog pathway, which primarily serves to counter GLI repression by processing GLI proteins into transcriptional activators. In investigating the mechanisms underlying GLI repression, we find that a subset of GLI binding regions, termed HH-responsive enhancers, specifically loses acetylation in the absence of HH signaling. These regions are highly enriched around HH target genes and primarily drive HH-specific transcriptional activity in the mouse limb bud. They also retain H3K27ac enrichment in limb buds devoid of GLI activator and repressor, indicating that their activity is primarily regulated by GLI repression. Furthermore, the Polycomb repression complex is not active at most of these regions, suggesting it is not a major mechanism of GLI repression. We propose a model for tissue-specific enhancer activity in which an HDAC-associated GLI repression complex regulates target genes by altering the acetylation status at enhancers.


Assuntos
Desenvolvimento Embrionário/fisiologia , Proteínas Hedgehog/metabolismo , Botões de Extremidades/metabolismo , Proteínas do Tecido Nervoso/metabolismo , Transativadores/metabolismo , Animais , Desenvolvimento Embrionário/genética , Regulação da Expressão Gênica no Desenvolvimento , Proteínas Hedgehog/genética , Histonas/metabolismo , Camundongos , Camundongos Knockout , Células NIH 3T3 , Proteínas do Tecido Nervoso/genética , Proteína Gli3 com Dedos de Zinco/genética , Proteína Gli3 com Dedos de Zinco/metabolismo
12.
Clin Cancer Res ; 26(6): 1327-1337, 2020 03 15.
Artigo em Inglês | MEDLINE | ID: mdl-31754049

RESUMO

PURPOSE: Neoadjuvant PD-1 blockade is a promising treatment for resectable non-small cell lung cancer (NSCLC), yet immunologic mechanisms contributing to tumor regression and biomarkers of response are unknown. Using paired tumor/blood samples from a phase II clinical trial (NCT02259621), we explored whether the peripheral T-cell clonotypic dynamics can serve as a biomarker for response to neoadjuvant PD-1 blockade. EXPERIMENTAL DESIGN: T-cell receptor (TCR) sequencing was performed on serial peripheral blood, tumor, and normal lung samples from resectable NSCLC patients treated with neoadjuvant PD-1 blockade. We explored the temporal dynamics of the T-cell repertoire in the peripheral and tumoral compartments in response to neoadjuvant PD-1 blockade by using the TCR as a molecular barcode. RESULTS: Higher intratumoral TCR clonality was associated with reduced percent residual tumor at the time of surgery, and the TCR repertoire of tumors with major pathologic response (MPR; <10% residual tumor after neoadjuvant therapy) had a higher clonality and greater sharing of tumor-infiltrating clonotypes with the peripheral blood relative to tumors without MPR. Additionally, the posttreatment tumor bed of patients with MPR was enriched with T-cell clones that had peripherally expanded between weeks 2 and 4 after anti-PD-1 initiation and the intratumoral space occupied by these clonotypes was inversely correlated with percent residual tumor. CONCLUSIONS: Our study suggests that exchange of T-cell clones between tumor and blood represents a key correlate of pathologic response to neoadjuvant immunotherapy and shows that the periphery may be a previously underappreciated originating compartment for effective antitumor immunity.See related commentary by Henick, p. 1205.


Assuntos
Carcinoma Pulmonar de Células não Pequenas , Neoplasias Pulmonares , Carcinoma Pulmonar de Células não Pequenas/tratamento farmacológico , Carcinoma Pulmonar de Células não Pequenas/genética , Humanos , Neoplasias Pulmonares/tratamento farmacológico , Neoplasias Pulmonares/genética , Terapia Neoadjuvante , Receptor de Morte Celular Programada 1 , Linfócitos T
13.
Methods Enzymol ; 629: 443-464, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31727253

RESUMO

Anti-tumor T cells are the soldiers in the body's war against cancer. Effector T cells can detect and eliminate cells expressing their cognate antigen via activation through engagement of the T cell receptor (TCR) with its cognate peptide:MHC complex. Owing to the recent success of immunotherapy in the treatment of many different cancer types, research efforts have shifted toward identifying and tracking anti-tumor T cell responses upon treatment in cancer patients. While traditional methods, such as ELISpot and flow cytometric intracellular staining have had limited success, likely owing to the inability to get viable biospecimens or the lower magnitude of tumor-specific T cell responses relative to virus-specific responses, new techniques that utilize next generation sequencing enable T cell response tracking independent of cytokine production or cell viability. The TCR, which confers T cell antigen-specificity, can be used as a molecular barcode to track T cell clonotypic dynamics across biological compartments and over time in cancer patients undergoing treatment. Because this method does not require viable cells, these T cell clonotypes can also be tracked in archival tumor tissue and flash frozen cell pellets. While exciting, quantitative TCR sequencing (TCRseq) technologies have been met with the conundrum of how to properly analyze and interpret the data. Here we provide a comprehensive guide on how to acquire, analyze, and interpret TCRseq data, as well as special considerations that should be taken prior to experimental setup.


Assuntos
Sequenciamento de Nucleotídeos em Larga Escala/métodos , Neoplasias/imunologia , Receptores de Antígenos de Linfócitos T/genética , Linfócitos T/imunologia , Imunidade Adaptativa/genética , Antígenos de Neoplasias/genética , Antígenos de Neoplasias/imunologia , Biologia Computacional/métodos , Epitopos de Linfócito T/genética , Epitopos de Linfócito T/imunologia , Sequenciamento de Nucleotídeos em Larga Escala/instrumentação , Humanos , Neoplasias/genética , Neoplasias/patologia , Receptores de Antígenos de Linfócitos T/imunologia , Receptores de Antígenos de Linfócitos T/metabolismo , Análise de Sequência de DNA/instrumentação , Análise de Sequência de DNA/métodos , Análise de Sequência de RNA/instrumentação , Análise de Sequência de RNA/métodos , Linfócitos T/metabolismo
14.
Immunity ; 51(5): 840-855.e5, 2019 11 19.
Artigo em Inglês | MEDLINE | ID: mdl-31606264

RESUMO

TCF-1 is a key transcription factor in progenitor exhausted CD8 T cells (Tex). Moreover, this Tex cell subset mediates responses to PD-1 checkpoint pathway blockade. However, the role of the transcription factor TCF-1 in early fate decisions and initial generation of Tex cells is unclear. Single-cell RNA sequencing (scRNA-seq) and lineage tracing identified a TCF-1+Ly108+PD-1+ CD8 T cell population that seeds development of mature Tex cells early during chronic infection. TCF-1 mediated the bifurcation between divergent fates, repressing development of terminal KLRG1Hi effectors while fostering KLRG1Lo Tex precursor cells, and PD-1 stabilized this TCF-1+ Tex precursor cell pool. TCF-1 mediated a T-bet-to-Eomes transcription factor transition in Tex precursors by promoting Eomes expression and drove c-Myb expression that controlled Bcl-2 and survival. These data define a role for TCF-1 in early-fate-bifurcation-driving Tex precursor cells and also identify PD-1 as a protector of this early TCF-1 subset.


Assuntos
Linfócitos T CD8-Positivos/metabolismo , Redes Reguladoras de Genes , Fator 1 de Transcrição de Linfócitos T/metabolismo , Transcrição Genética , Animais , Linfócitos T CD8-Positivos/imunologia , Diferenciação Celular/genética , Diferenciação Celular/imunologia , Doença Crônica , Perfilação da Expressão Gênica , Interações Hospedeiro-Patógeno/genética , Interações Hospedeiro-Patógeno/imunologia , Camundongos , Receptor de Morte Celular Programada 1/metabolismo , Fator 1 de Transcrição de Linfócitos T/genética , Viroses/genética , Viroses/imunologia , Viroses/virologia
15.
Nucleic Acids Res ; 47(19): e121, 2019 11 04.
Artigo em Inglês | MEDLINE | ID: mdl-31428792

RESUMO

Conventional high-throughput genomic technologies for mapping regulatory element activities in bulk samples such as ChIP-seq, DNase-seq and FAIRE-seq cannot analyze samples with small numbers of cells. The recently developed low-input and single-cell regulome mapping technologies such as ATAC-seq and single-cell ATAC-seq (scATAC-seq) allow analyses of small-cell-number and single-cell samples, but their signals remain highly discrete or noisy. Compared to these regulome mapping technologies, transcriptome profiling by RNA-seq is more widely used. Transcriptome data in single-cell and small-cell-number samples are more continuous and often less noisy. Here, we show that one can globally predict chromatin accessibility and infer regulatory element activities using RNA-seq. Genome-wide chromatin accessibility predicted by RNA-seq from 30 cells can offer better accuracy than ATAC-seq from 500 cells. Predictions based on single-cell RNA-seq (scRNA-seq) can more accurately reconstruct bulk chromatin accessibility than using scATAC-seq. Integrating ATAC-seq with predictions from RNA-seq increases the power and value of both methods. Thus, transcriptome-based prediction provides a new tool for decoding gene regulatory circuitry in samples with limited cell numbers.


Assuntos
Cromatina/genética , Sequenciamento de Nucleotídeos em Larga Escala/métodos , RNA/genética , Análise de Célula Única/métodos , Cromatina/química , Biologia Computacional , Genoma/genética , Humanos , Sequências Reguladoras de Ácido Nucleico/genética , Análise de Sequência de DNA , Transcriptoma/genética , Transposases/genética
16.
BMC Genomics ; 20(1): 147, 2019 Feb 19.
Artigo em Inglês | MEDLINE | ID: mdl-30782122

RESUMO

BACKGROUND: Pain is a subjective experience derived from complex interactions among biological, environmental, and psychosocial pathways. Sex differences in pain sensitivity and chronic pain prevalence are well established. However, the molecular basis underlying these sex dimorphisms are poorly understood particularly with regard to the role of the peripheral nervous system. Here we sought to identify shared and distinct gene networks functioning in the peripheral nervous systems that may contribute to sex differences of pain in rats after nerve injury. RESULTS: We performed RNA-seq on dorsal root ganglia following chronic constriction injury of the sciatic nerve in male and female rats. Analysis from paired naive and injured tissues showed that 1513 genes were differentially expressed between sexes. Genes which facilitated synaptic transmission in naïve and injured females did not show increased expression in males. CONCLUSIONS: Appreciating sex-related gene expression differences and similarities in neuropathic pain models may help to improve the translational relevance to clinical populations and efficacy of clinical trials of this major health issue.


Assuntos
Gânglios Espinais/metabolismo , Gânglios Espinais/patologia , Regulação da Expressão Gênica , Traumatismos dos Nervos Periféricos/etiologia , Animais , Feminino , Perfilação da Expressão Gênica , Masculino , Traumatismos dos Nervos Periféricos/metabolismo , Traumatismos dos Nervos Periféricos/patologia , Ratos , Fatores Sexuais , Transcriptoma
17.
Methods Mol Biol ; 1935: 115-124, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-30758823

RESUMO

In many single-cell RNA-seq (scRNA-seq) experiments, cells represent progressively changing states along a continuous biological process. A useful approach to analyzing data from such experiments is to computationally order cells based on their gradual transition of gene expression. The ordered cells can be viewed as samples drawn from a pseudo-temporal trajectory. Analyzing gene expression dynamics along the pseudotime provides a valuable tool for reconstructing the underlying biological process and generating biological insights. TSCAN is an R package to support in silico reconstruction of cells' pseudotime. This chapter introduces how to apply TSCAN to scRNA-seq data to perform pseudotime analysis.


Assuntos
RNA/genética , Análise de Sequência de RNA/métodos , Análise de Célula Única/métodos , Biologia Computacional/métodos , Expressão Gênica/genética , Perfilação da Expressão Gênica/métodos , Sequenciamento de Nucleotídeos em Larga Escala/métodos , Humanos , Software
18.
Nucleic Acids Res ; 46(1): e2, 2018 01 09.
Artigo em Inglês | MEDLINE | ID: mdl-29325176

RESUMO

Biological processes are usually associated with genome-wide remodeling of transcription driven by transcription factors (TFs). Identifying key TFs and their spatiotemporal binding patterns are indispensable to understanding how dynamic processes are programmed. However, most methods are designed to predict TF binding sites only. We present a computational method, dynamic motif occupancy analysis (DynaMO), to infer important TFs and their spatiotemporal binding activities in dynamic biological processes using chromatin profiling data from multiple biological conditions such as time-course histone modification ChIP-seq data. In the first step, DynaMO predicts TF binding sites with a random forests approach. Next and uniquely, DynaMO infers dynamic TF binding activities at predicted binding sites using their local chromatin profiles from multiple biological conditions. Another landmark of DynaMO is to identify key TFs in a dynamic process using a clustering and enrichment analysis of dynamic TF binding patterns. Application of DynaMO to the yeast ultradian cycle, mouse circadian clock and human neural differentiation exhibits its accuracy and versatility. We anticipate DynaMO will be generally useful for elucidating transcriptional programs in dynamic processes.


Assuntos
Algoritmos , Fenômenos Biológicos/genética , Biologia Computacional/métodos , Motivos de Nucleotídeos/genética , Fatores de Transcrição/metabolismo , Animais , Sequência de Bases , Sítios de Ligação/genética , Diferenciação Celular/genética , Cromatina/genética , Cromatina/metabolismo , Imunoprecipitação da Cromatina , Humanos , Camundongos , Neurônios/citologia , Neurônios/metabolismo , Ligação Proteica
19.
Nat Commun ; 8(1): 1038, 2017 10 19.
Artigo em Inglês | MEDLINE | ID: mdl-29051481

RESUMO

We evaluate the feasibility of using a biological sample's transcriptome to predict its genome-wide regulatory element activities measured by DNase I hypersensitivity (DH). We develop BIRD, Big Data Regression for predicting DH, to handle this high-dimensional problem. Applying BIRD to the Encyclopedia of DNA Elements (ENCODE) data, we found that to a large extent gene expression predicts DH, and information useful for prediction is contained in the whole transcriptome rather than limited to a regulatory element's neighboring genes. We show applications of BIRD-predicted DH in predicting transcription factor-binding sites (TFBSs), turning publicly available gene expression samples in Gene Expression Omnibus (GEO) into a regulome database, predicting differential regulatory element activities, and facilitating regulome data analyses by serving as pseudo-replicates. Besides improving our understanding of the regulome-transcriptome relationship, this study suggests that transcriptome-based prediction can provide a useful new approach for regulome mapping.


Assuntos
Desoxirribonuclease I/metabolismo , Genoma Humano , Bases de Dados Genéticas , Perfilação da Expressão Gênica , Genômica , Humanos , Transcriptoma
20.
Bioinformatics ; 33(18): 2930-2932, 2017 Sep 15.
Artigo em Inglês | MEDLINE | ID: mdl-28505247

RESUMO

Summary: Emerging single-cell technologies (e.g. single-cell ATAC-seq, DNase-seq or ChIP-seq) have made it possible to assay regulome of individual cells. Single-cell regulome data are highly sparse and discrete. Analyzing such data is challenging. User-friendly software tools are still lacking. We present SCRAT, a Single-Cell Regulome Analysis Toolbox with a graphical user interface, for studying cell heterogeneity using single-cell regulome data. SCRAT can be used to conveniently summarize regulatory activities according to different features (e.g. gene sets, transcription factor binding motif sites, etc.). Using these features, users can identify cell subpopulations in a heterogeneous biological sample, infer cell identities of each subpopulation, and discover distinguishing features such as gene sets and transcription factors that show different activities among subpopulations. Availability and implementation: SCRAT is freely available at https://zhiji.shinyapps.io/scrat as an online web service and at https://github.com/zji90/SCRAT as an R package. Contact: hji@jhu.edu. Supplementary information: Supplementary data are available at Bioinformatics online.


Assuntos
Biologia Computacional/métodos , Regulação da Expressão Gênica , Regiões Promotoras Genéticas , Análise de Célula Única/métodos , Software , Fatores de Transcrição/metabolismo , Animais , DNA/metabolismo , Células-Tronco Embrionárias/metabolismo , Humanos , Camundongos
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