Modeling Spatio-temporal Dynamics of Chromatin Marks

Mapping Intimacies ◽

10.1101/239442 ◽

2017 ◽

Author(s):

Petko Fiziev ◽

Jason Ernst

Keyword(s):

Gene Expression ◽

Time Course ◽

Temporal Dynamics ◽

Spatial Dynamics ◽

Computational Method ◽

Time Points ◽

Signal Density ◽

Spatial Changes ◽

Spatio Temporal ◽

Over Time

ABSTRACTTo model spatial changes of chromatin mark peaks over time we developed and applied ChromTime, a computational method that predicts regions for which peaks either expand or contract significantly or hold steady between time points. Predicted expanding and contracting peaks can mark regulatory regions associated with transcription factor binding and gene expression changes. Spatial dynamics of peaks provided information about gene expression changes beyond localized signal density changes. ChromTime detected asymmetric expansions and contractions, which for some marks associated with the direction of transcription. ChromTime facilitates the analysis of time course chromatin data in a range of biological systems.

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Bayesian approach for predicting responses to therapy from high-dimensional time-course gene expression profiles

BMC Bioinformatics ◽

10.1186/s12859-021-04052-4 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Arika Fukushima ◽

Masahiro Sugimoto ◽

Satoru Hiwa ◽

Tomoyuki Hiroyasu

Keyword(s):

Gene Expression ◽

Time Course ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Response To Therapy ◽

Hcv Infection ◽

Entire Treatment Period ◽

Time Points ◽

Time Course Data ◽

Conventional Methods

Abstract Background Historical and updated information provided by time-course data collected during an entire treatment period proves to be more useful than information provided by single-point data. Accurate predictions made using time-course data on multiple biomarkers that indicate a patient’s response to therapy contribute positively to the decision-making process associated with designing effective treatment programs for various diseases. Therefore, the development of prediction methods incorporating time-course data on multiple markers is necessary. Results We proposed new methods that may be used for prediction and gene selection via time-course gene expression profiles. Our prediction method consolidated multiple probabilities calculated using gene expression profiles collected over a series of time points to predict therapy response. Using two data sets collected from patients with hepatitis C virus (HCV) infection and multiple sclerosis (MS), we performed numerical experiments that predicted response to therapy and evaluated their accuracies. Our methods were more accurate than conventional methods and successfully selected genes, the functions of which were associated with the pathology of HCV infection and MS. Conclusions The proposed method accurately predicted response to therapy using data at multiple time points. It showed higher accuracies at early time points compared to those of conventional methods. Furthermore, this method successfully selected genes that were directly associated with diseases.

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Jonckheere–Terpstra–Kendall-based non-parametric analysis of temporal differential gene expression

NAR Genomics and Bioinformatics ◽

10.1093/nargab/lqab021 ◽

2021 ◽

Vol 3 (1) ◽

Author(s):

Hitoshi Iuchi ◽

Michiaki Hamada

Keyword(s):

Gene Expression ◽

Time Series ◽

Time Course ◽

Time Series Data ◽

Expression Patterns ◽

Detection Methods ◽

Series Data ◽

Expression Levels ◽

Over Time ◽

Non Parametric

Abstract Time-course experiments using parallel sequencers have the potential to uncover gradual changes in cells over time that cannot be observed in a two-point comparison. An essential step in time-series data analysis is the identification of temporal differentially expressed genes (TEGs) under two conditions (e.g. control versus case). Model-based approaches, which are typical TEG detection methods, often set one parameter (e.g. degree or degree of freedom) for one dataset. This approach risks modeling of linearly increasing genes with higher-order functions, or fitting of cyclic gene expression with linear functions, thereby leading to false positives/negatives. Here, we present a Jonckheere–Terpstra–Kendall (JTK)-based non-parametric algorithm for TEG detection. Benchmarks, using simulation data, show that the JTK-based approach outperforms existing methods, especially in long time-series experiments. Additionally, application of JTK in the analysis of time-series RNA-seq data from seven tissue types, across developmental stages in mouse and rat, suggested that the wave pattern contributes to the TEG identification of JTK, not the difference in expression levels. This result suggests that JTK is a suitable algorithm when focusing on expression patterns over time rather than expression levels, such as comparisons between different species. These results show that JTK is an excellent candidate for TEG detection.

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Temporal gene expression in bovine corpora lutea after treatment with PGF2alpha based on serial biopsies in vivo

Reproduction ◽

10.1530/rep.0.1210905 ◽

2001 ◽

pp. 905-913 ◽

Cited By ~ 38

Author(s):

SJ Tsai ◽

K Kot ◽

OJ Ginther ◽

MC Wiltbank

Keyword(s):

Gene Expression ◽

Corpus Luteum ◽

Time Course ◽

Regulatory Protein ◽

Corpora Lutea ◽

Multiple Time ◽

Lh Receptor ◽

Time Points ◽

Multiple Biopsies ◽

Fp Receptor

There is growing evidence to indicate that PGF(2alpha)-induced luteolysis involves altered gene expression in the corpus luteum. Concentrations of mRNA encoding nine different gene products were quantified at three time points from corpora lutea in situ. Serial luteal biopsies (2.1-5.5 mg per biopsy) were collected using an ultrasound-guided transvaginal method and mRNA concentrations were quantified with standard curve quantitative competitive RT-PCR. In the first experiment, three luteal biopsies were collected from three heifers and analysed in multiple assays to evaluate the repeatability of the methods. Concentrations of mRNA for glyceraldehyde 3-phosphate dehydrogenase (GAPDH), PGF(2alpha) receptor (FP receptor) and LH receptor were found to be highly repeatable between assays, between multiple biopsies and between animals (coefficients of variation 1.3-17.3%). In the second experiment, heifers on days 9-11 after ovulation were assigned randomly to receive saline only (n = 6), saline with biopsies taken at t = 0, 0.5 and 4.0 h after injection (n = 6), PGF(2alpha) only (n = 6) or PGF(2alpha) with biopsies taken at t = 0, 0.5 and 4.0 h after treatment (n = 7). Biopsy alone did not change corpus luteum diameter, serum progesterone concentrations or days to next ovulation within the saline- or PGF(2alpha)-treated groups. Concentrations of mRNA for steroidogenic acute regulatory protein, FP receptor, 3beta-hydroxysteroid dehydrogenase, cytosolic phospholipase A(2) and LH receptor were decreased at 4.0 h after PGF(2alpha) injection. In contrast, PGF(2alpha) increased mRNA concentrations for prostaglandin G/H synthase-2, monocyte chemoattractant protein-1 and c-fos but the time course differed for induction of these mRNAs. Concentrations of mRNA for GAPDH did not change after PGF(2alpha) treatment. In conclusion, the techniques allowed analysis of multiple, specific mRNAs in an individual corpus luteum at multiple time points without altering subsequent luteal function. Use of these techniques confirmed that luteolysis involves both up- and downregulation of specific mRNA by PGF(2alpha).

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A sensitive mNeonGreen reporter system to measure transcriptional dynamics in Drosophila development

Communications Biology ◽

10.1038/s42003-020-01375-5 ◽

2020 ◽

Vol 3 (1) ◽

Author(s):

Stefano Ceolin ◽

Monika Hanf ◽

Marta Bozek ◽

Andrea Ennio Storti ◽

Nicolas Gompel ◽

...

Keyword(s):

Gene Expression ◽

Fluorescent Protein ◽

Temporal Dynamics ◽

Reconstruction Algorithm ◽

Detection Sensitivity ◽

Axis Formation ◽

Reporter System ◽

Enhancer Activity ◽

Spatio Temporal ◽

Pioneer Transcription Factor

AbstractThe gene regulatory network governing anterior–posterior axis formation in Drosophila is a well-established paradigm to study transcription in developmental biology. The rapid temporal dynamics of gene expression during early stages of development, however, are difficult to track with standard techniques. We optimized the bright and fast-maturing fluorescent protein mNeonGreen as a real-time, quantitative reporter of enhancer expression. We derive enhancer activity from the reporter fluorescence dynamics with high spatial and temporal resolution, using a robust reconstruction algorithm. By comparing our results with data obtained with the established MS2-MCP system, we demonstrate the higher detection sensitivity of our reporter. We used the reporter to quantify the activity of variants of a simple synthetic enhancer, and observe increased activity upon reduction of enhancer–promoter distance or addition of binding sites for the pioneer transcription factor Zelda. Our reporter system constitutes a powerful tool to study spatio-temporal gene expression dynamics in live embryos.

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Hot spot detection and spatio-temporal dynamics of dengue in Queensland, Australia

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprsarchives-xl-8-197-2014 ◽

2014 ◽

Vol XL-8 ◽

pp. 197-204 ◽

Cited By ~ 6

Author(s):

S. Naish ◽

S. Tong

Keyword(s):

Temporal Variation ◽

Temporal Dynamics ◽

Hot Spot ◽

Seasonal Pattern ◽

Temporal Distribution ◽

Health Concern ◽

Spatial And Temporal Variation ◽

Dengue Case ◽

Spatio Temporal ◽

Over Time

Dengue has been a major public health concern in Australia since it re-emerged in Queensland in 1992–1993. This study explored spatio-temporal distribution and clustering of locally-acquired dengue cases in Queensland State, Australia and identified target areas for effective interventions. A computerised locally-acquired dengue case dataset was collected from Queensland Health for Queensland from 1993 to 2012. Descriptive spatial and temporal analyses were conducted using geographic information system tools and geostatistical techniques. Dengue hot spots were detected using SatScan method. Descriptive spatial analysis showed that a total of 2,398 locally-acquired dengue cases were recorded in central and northern regions of tropical Queensland. A seasonal pattern was observed with most of the cases occurring in autumn. Spatial and temporal variation of dengue cases was observed in the geographic areas affected by dengue over time. Tropical areas are potential high-risk areas for mosquito-borne diseases such as dengue. This study demonstrated that the locally-acquired dengue cases have exhibited a spatial and temporal variation over the past twenty years in tropical Queensland, Australia. There is a clear evidence for the existence of statistically significant clusters of dengue and these clusters varied over time. These findings enabled us to detect and target dengue clusters suggesting that the use of geospatial information can assist the health authority in planning dengue control activities and it would allow for better design and implementation of dengue management programs.

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Spatio-temporal dynamics of gene expression of the Edn1-Dlx5/6 pathway during development of the lower jaw

genesis ◽

10.1002/dvg.20625 ◽

2010 ◽

Vol 48 (6) ◽

pp. 262-373 ◽

Cited By ~ 18

Author(s):

Maxence Vieux-Rochas ◽

Stefano Mantero ◽

Eglantine Heude ◽

Ottavia Barbieri ◽

Simonetta Astigiano ◽

...

Keyword(s):

Gene Expression ◽

Temporal Dynamics ◽

Lower Jaw ◽

Spatio Temporal

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Abstract P744: Gene Transcript Clusters Distinguish Time-Dependent Expression Patterns in Monocytes, Neutrophils and Whole Blood After Ischemic Stroke Injury

Stroke ◽

10.1161/str.52.suppl_1.p744 ◽

2021 ◽

Vol 52 (Suppl_1) ◽

Author(s):

Paulina Carmona-Mora ◽

Glen C Jickling ◽

Xinhua Zhan ◽

Marisa Hakoupian ◽

Heather Hull ◽

...

Keyword(s):

Gene Expression ◽

Ischemic Stroke ◽

Whole Blood ◽

Temporal Dynamics ◽

Expression Profiles ◽

Expression Patterns ◽

Gene Expression Profiles ◽

Time Dependent ◽

Gene Transcript ◽

Time Points

Introduction: After ischemic stroke (IS), peripheral leukocytes infiltrate the damaged region and modulate the response to injury. We previously showed that peripheral blood cells display different gene expression profiles after IS and these transcriptional programs reflect the changes in immune processes in response to IS. Dissecting the temporal dynamics of gene expression after IS improves our understanding of the changes of molecular and cellular pathways involved in acute brain injury. Methods: We analyzed the transcriptomic profiles of 33 IS patients in isolated monocytes, neutrophils and whole blood. RNA-sequencing was performed on all the stroke samples as well as 12 controls with vascular risk factors (diabetes and/or hypertension and/or hypercholesterolemia). To identify differentially expressed genes, subjects were split into time points (TPs) from stroke onset (TP1= 0-24 h; TP2= 24-48 h; and TP3= > 48 h), and controls were assigned TP0. A linear regression model including time and the interaction of diagnosis x TP with cutoff of p<0.02 and fold-change>|1.2| was used. Time dependent changes were analyzed using artificial neural networks to identify clusters of genes that behave in a similar way across TPs. Results: Unique patterns of temporal expression were distinguished for the three sample types. These include genes not expressed in TP0 that peak only within the first 24 h, others that peak or decrease in TP2 and TP3, and more complex patterns. Genes that peak at TP1 in monocytes and neutrophils are related to cell adhesion and leukocyte differentiation/migration, respectively. Early peaks in whole blood occur in genes related to transcriptional regulation. In monocytes, interleukin pathways are enriched across all TPs, whereas there is a trend of suppression after 24 h in neutrophils. The inflammasome pathway is enriched in the earlier TPs in neutrophils, while not enriched in monocytes until over 48 hours. Conclusion: Our analyses on gene expression dynamics and cluster patterns allow identification of key genes and pathways at different time points following ischemic injury that are valuable as IS biomarkers and may be possible treatment targets.

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Time Course of Microbiologic Outcome and Gene Expression in Candida albicans during and following In Vitro and In Vivo Exposure to Fluconazole

Antimicrobial Agents and Chemotherapy ◽

10.1128/aac.50.4.1311-1319.2006 ◽

2006 ◽

Vol 50 (4) ◽

pp. 1311-1319 ◽

Cited By ~ 27

Author(s):

A. Lepak ◽

J. Nett ◽

L. Lincoln ◽

K. Marchillo ◽

D. Andes

Keyword(s):

Gene Expression ◽

Candida Albicans ◽

Time Course ◽

Dependent Manner ◽

Time Points ◽

In Vivo Expression ◽

The Impact ◽

The Relationship

ABSTRACT Pharmacodynamics (PD) considers the relationship between drug exposure and effect. The two factors that have been used to distinguish the PD behaviors of antimicrobials are the impact of concentration on the extent of organism killing and the duration of persistent microbiologic suppression (postantibiotic effect). The goals of these studies were (i) to examine the relationship between antimicrobial PD and gene expression and (ii) to gain insight into the mechanism of fluconazole effects persisting following exposure. Microarrays were used to estimate the transcriptional response of Candida albicans to a supra-MIC F exposure over time in vitro. Fluconazole at four times the MIC was added to a log-phase C. albicans culture, and cells were collected to determine viable growth and for microarray analyses. We identified differential expression of 18% of all genes for at least one of the time points. More genes were upregulated (n = 1,053 [16%]) than downregulated (174 [3%]). Of genes with known function that were upregulated during exposure, most were related to plasma membrane/cell wall synthesis (18%), stress responses (7%), and metabolism (6%). The categories of downregulated genes during exposure included protein synthesis (15%), DNA synthesis/repair (7%), and transport (7%) genes. The majority of genes identified at the postexposure time points were from the protein (17%) and DNA (7%) synthesis categories. In subsequent studies, three genes (CDR1, CDR2, and ERG11) were examined in greater detail (more concentration and time points) following fluconazole exposure in vitro and in vivo. Expression levels from the in vitro and in vivo studies were congruent. CDR1 and CDR2 transcripts were reduced during in vitro fluconazole exposure and during supra-MIC exposure in vivo. However, in the postexposure period, the mRNA abundance of both pumps increased. ERG11 expression increased during exposure and fell in the postexposure period. The expression of the three genes responded in a dose-dependent manner. In sum, the microarray data obtained during and following fluconazole exposure identified genes both known and unknown to be affected by this drug class. The expanded in vitro and in vivo expression data set underscores the importance of considering the time course of exposure in pharmacogenomic investigations.

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Genomic DNA microarray comparison of gene expression patterns in Paracoccidioides brasiliensis mycelia and yeasts in vitro

Microbiology ◽

10.1099/mic.0.027441-0 ◽

2009 ◽

Vol 155 (8) ◽

pp. 2795-2808 ◽

Cited By ~ 23

Author(s):

Jomar Patrício Monteiro ◽

Karl V. Clemons ◽

Laurence F. Mirels ◽

John A. Coller ◽

Thomas D. Wu ◽

...

Keyword(s):

Gene Expression ◽

Transcription Factors ◽

Genomic Dna ◽

Paracoccidioides Brasiliensis ◽

Expression Patterns ◽

Gene Expression Patterns ◽

Protein Catabolism ◽

Time Points ◽

Over Time

Paracoccidioides brasiliensis is a thermally dimorphic fungus, and causes the most prevalent systemic mycosis in Latin America. Infection is initiated by inhalation of conidia or mycelial fragments by the host, followed by further differentiation into the yeast form. Information regarding gene expression by either form has rarely been addressed with respect to multiple time points of growth in culture. Here, we report on the construction of a genomic DNA microarray, covering approximately 25 % of the genome of the organism, and its utilization in identifying genes and gene expression patterns during growth in vitro. Cloned, amplified inserts from randomly sheared genomic DNA (gDNA) and known control genes were printed onto glass slides to generate a microarray of over 12 000 elements. To examine gene expression, mRNA was extracted and amplified from mycelial or yeast cultures grown in semi-defined medium for 5, 8 and 14 days. Principal components analysis and hierarchical clustering indicated that yeast gene expression profiles differed greatly from those of mycelia, especially at earlier time points, and that mycelial gene expression changed less than gene expression in yeasts over time. Genes upregulated in yeasts were found to encode proteins shown to be involved in methionine/cysteine metabolism, respiratory and metabolic processes (of sugars, amino acids, proteins and lipids), transporters (small peptides, sugars, ions and toxins), regulatory proteins and transcription factors. Mycelial genes involved in processes such as cell division, protein catabolism, nucleotide biosynthesis and toxin and sugar transport showed differential expression. Sequenced clones were compared with Histoplasma capsulatum and Coccidioides posadasii genome sequences to assess potentially common pathways across species, such as sulfur and lipid metabolism, amino acid transporters, transcription factors and genes possibly related to virulence. We also analysed gene expression with time in culture and found that while transposable elements and components of respiratory pathways tended to increase in expression with time, genes encoding ribosomal structural proteins and protein catabolism tended to sharply decrease in expression over time, particularly in yeast. These findings expand our knowledge of the different morphological forms of P. brasiliensis during growth in culture.

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