A top-down measure of gene-to-gene coordination for analyzing cell-to-cell variability

AbstractRecent technological advances, such as single-cell RNA sequencing (scRNA-seq), allow the measurement of gene expression profiles of individual cells. These expression profiles typically exhibit substantial variations even across seemingly homogeneous populations of cells. Two main different sources contribute to this measured variability: actual differences between the biological activity of the cells and technical measurement errors. Analysis of the biological variability may provide information about the underlying gene regulation of the cells, yet distinguishing it from the technical variability is a challenge. Here, we apply a recently developed computational method for measuring the global gene coordination level (GCL) to systematically study the cell-to-cell variability in numerical models of gene regulation. We simulate ‘biological variability’ by introducing heterogeneity in the underlying regulatory dynamic of different cells, while ‘technical variability’ is represented by stochastic measurement noise. We show that the GCL decreases for cohorts of cells with increased ‘biological variability’ only when it is originated from the interactions between the genes. Moreover, we find that the GCL can evaluate and compare—for cohorts with the same cell-to-cell variability—the ratio between the introduced biological and technical variability. Finally, we show that the GCL is robust against spurious correlations that originate from a small sample size or from the compositionality of the data. The presented methodology can be useful for future analysis of high-dimensional ecological and biochemical dynamics.

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Distinctive gene expression profiles of CD34 cells from patients with myelodysplastic syndrome characterized by specific chromosomal abnormalities

Blood ◽

10.1182/blood-2004-01-0103 ◽

2004 ◽

Vol 104 (13) ◽

pp. 4210-4218 ◽

Cited By ~ 104

Author(s):

Guibin Chen ◽

Weihua Zeng ◽

Akira Miyazato ◽

Eric Billings ◽

Jaroslaw P. Maciejewski ◽

...

Keyword(s):

Gene Expression ◽

Molecular Mechanisms ◽

Expression Profiles ◽

Small Sample ◽

Hematopoietic Progenitor Cell ◽

Molecular Characteristics ◽

Hematopoietic Progenitor ◽

Trisomy 8 ◽

Monosomy 7 ◽

Cd34 Cells

Abstract Aneuploidy, especially monosomy 7 and trisomy 8, is a frequent cytogenetic abnormality in the myelodysplastic syndromes (MDSs). Patients with monosomy 7 and trisomy 8 have distinctly different clinical courses, responses to therapy, and survival probabilities. To determine disease-specific molecular characteristics, we analyzed the gene expression pattern in purified CD34 hematopoietic progenitor cells obtained from MDS patients with monosomy 7 and trisomy 8 using Affymetrix GeneChips. Two methods were employed: standard hybridization and a small-sample RNA amplification protocol for the limited amounts of RNA available from individual cases; results were comparable between these 2 techniques. Microarray data were confirmed by gene amplification and flow cytometry using individual patient samples. Genes related to hematopoietic progenitor cell proliferation and blood cell function were dysregulated in CD34 cells of both monosomy 7 and trisomy 8 MDS. In trisomy 8, up-regulated genes were primarily involved in immune and inflammatory responses, and down-regulated genes have been implicated in apoptosis inhibition. CD34 cells in monosomy 7 showed up-regulation of genes inducing leukemia transformation and tumorigenesis and apoptosis and down-regulation of genes controlling cell growth and differentiation. These results imply distinct molecular mechanisms for monosomy 7 and trisomy 8 MDS and implicate specific pathogenic pathways.

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Prognostic Significance of in situ Phenotypic Marker Expression in Diffuse Large B-cell Lymphomas

Biomarker Insights ◽

10.1177/117727190700200009 ◽

2007 ◽

Vol 2 ◽

pp. 117727190700200 ◽

Cited By ~ 4

Author(s):

Alexandar Tzankov ◽

Philip Went ◽

Stephan Dirnhofer

Keyword(s):

B Cell ◽

Expression Profiles ◽

Prognostic Significance ◽

Gene Expression Profiles ◽

Small Sample ◽

B Cell Lymphomas ◽

Phenotypic Marker ◽

Small Sample Sizes ◽

Protein Expression Profiles ◽

Large B Cell

Diffuse large B-cell lymphomas (DLBCL) are the most common lymphoid malignancies, and encompass all malignant lymphomas characterized by large neoplastic cells and B-cell derivation. In the last decade, DLBCL has been subjected to intense clinical, phenotypic and molecular studies, and were found to represent a heterogeneous group of tumors. These studies suggested new disease subtypes and variants with distinct clinical characteristics, morphologies, immunophenotypes, genotypes or gene expression profiles, associated with distinct prognoses or unique sensitivities to particular therapy regimens. Unfortunately, the reliability and reproducibility of the molecular results remains unclear due to contradictory reports in the literature resulting from small sample sizes, referral and selection biases, and variable methodologies and cut-off levels used to determine positivity. Here, we review phenotypic studies on the prognostic significance of protein expression profiles in DLBCL and reconsider our own retrospective data on 301 primary DLBCL cases obtained on a previously validated tissue microarray in light of powerful statistical methods of determining optimal cut-off values of phenotypic factors for prediction of outcome.

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Integrated Analysis of microRNA and mRNA Expression Profiles: An Attempt to Disentangle the Complex Interaction Network in Attention Deficit Hyperactivity Disorder

Brain Sciences ◽

10.3390/brainsci9100288 ◽

2019 ◽

Vol 9 (10) ◽

pp. 288

Author(s):

Nicoletta Nuzziello ◽

Francesco Craig ◽

Marta Simone ◽

Arianna Consiglio ◽

Flavio Licciulli ◽

...

Keyword(s):

Attention Deficit Hyperactivity Disorder ◽

Mrna Expression ◽

Attention Deficit ◽

Expression Profiles ◽

Interaction Network ◽

Small Sample ◽

Integrated Analysis ◽

Children With Adhd ◽

Pathway Enrichment ◽

Hyperactivity Disorder

Attention Deficit Hyperactivity Disorder (ADHD) is a childhood-onset neurodevelopmental disorder, whose etiology and pathogenesis are still largely unknown. In order to uncover novel regulatory networks and molecular pathways possibly related to ADHD, we performed an integrated miRNA and mRNA expression profiling analysis in peripheral blood samples of children with ADHD and age-matched typically developing (TD) children. The expression levels of 13 miRNAs were evaluated with microfluidic qPCR, and differentially expressed (DE) mRNAs were detected on an Illumina HiSeq 2500 genome analyzer. The miRNA targetome was identified using an integrated approach of validated and predicted interaction data extracted from seven different bioinformatic tools. Gene Ontology (GO) and pathway enrichment analyses were carried out. Results showed that six miRNAs (miR-652-3p, miR-942-5p, let-7b-5p, miR-181a-5p, miR-320a, and miR-148b-3p) and 560 genes were significantly DE in children with ADHD compared to TD subjects. After correction for multiple testing, only three miRNAs (miR-652-3p, miR-148b-3p, and miR-942-5p) remained significant. Genes known to be associated with ADHD (e.g., B4GALT2, SLC6A9 TLE1, ANK3, TRIO, TAF1, and SYNE1) were confirmed to be significantly DE in our study. Integrated miRNA and mRNA expression data identified critical key hubs involved in ADHD. Finally, the GO and pathway enrichment analyses of all DE genes showed their deep involvement in immune functions, reinforcing the hypothesis that an immune imbalance might contribute to the ADHD etiology. Despite the relatively small sample size, in this study we were able to build a complex miRNA-target interaction network in children with ADHD that might help in deciphering the disease pathogenesis. Validation in larger samples should be performed in order to possibly suggest novel therapeutic strategies for treating this complex disease.

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Estimates of anthropogenic CO2 emissions from satellite and ground based measurements

10.5194/egusphere-egu2020-2580 ◽

2020 ◽

Author(s):

Yury Timofeyev ◽

George Nerobelov ◽

Sergey Smyshlyaev ◽

Ivan Berezin ◽

Yana Virolainen ◽

...

Keyword(s):

Measurement Errors ◽

Numerical Models ◽

Dispersion Model ◽

A Priori ◽

Three Dimensional ◽

Atmospheric Model ◽

Experimental Information ◽

Anthropogenic Emissions ◽

Plume Dispersion ◽

Satellite Measurements

In recent years, satellite methods have played an important role in CO2 monitoring. Various satellite instruments (SCIAMACHY, AIRS, GOSAT, OCO-2, etc.) validated by ground-based and aircraft measurements allow to retrieving the column averaged CO2 mixing ratio (XCO2) with high accuracy (0.25&#8211;1.0%). The relatively high spatial resolution of a number of instruments (for example, OCO-2) allows studies of spatial and temporal CO2 variations, that, under appropriate conditions, makes it possible to estimate anthropogenic emissions from different cities.Various techniques (source pixel mass balance method, plume dispersion model and atmospheric inversion system) for determining anthropogenic greenhouse gas emissions from data of satellite measurements are considered.On the basis of three-dimensional modeling and comparison with the results of various local and remote measurements, numerical models of the atmosphere were adapted to different megacities of Russia. Based on numerical experiments, the errors of various satellite techniques for determining emissions caused by various factors (measurement errors, quality of used a priori and additional experimental information, adequacy of used numerical atmospheric model, etc.) were evaluated. Anthropogenic CO2 emissions in St. Petersburg, Moscow and other cities of Russia are estimated using various satellite measurements. These estimates of anthropogenic emissions are compared with data obtained by different methods and for different cities.

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Effects of underlying gene-regulation network structure on prediction accuracy in high-dimensional regression

10.1101/2020.09.11.293456 ◽

2020 ◽

Author(s):

Yuichi Okinaga ◽

Daisuke Kyogoku ◽

Satoshi Kondo ◽

Atsushi J. Nagano ◽

Kei Hirose

Keyword(s):

Gene Regulation ◽

Prediction Accuracy ◽

Principal Component ◽

Small Sample ◽

Estimation Methods ◽

Estimation Accuracy ◽

High Dimensional ◽

Sample Sizes ◽

Gene Regulation Network ◽

Regulation Network

AbstractMotivationThe least absolute shrinkage and selection operator (lasso) and principal component regression (PCR) are popular methods of estimating traits from high-dimensional omics data, such as transcriptomes. The prediction accuracy of these estimation methods is highly dependent on the covariance structure, which is characterized by gene regulation networks. However, the manner in which the structure of a gene regulation network together with the sample size affects prediction accuracy has not yet been sufficiently investigated. In this study, Monte Carlo simulations are conducted to investigate the prediction accuracy for several network structures under various sample sizes.ResultsWhen the gene regulation network was random graph, the simulation indicated that models with high estimation accuracy could be achieved with small sample sizes. However, a real gene regulation network is likely to exhibit a scale-free structure. In such cases, the simulation indicated that a relatively large number of observations is required to accurately predict traits from a transcriptome.Availability and implementationSource code at https://github.com/keihirose/[email protected]

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MEASUREMENT ERRORS ANALYSIS OF THE UHF SIGNALS INSTANT FREQUENCY IN BRILLOUIN MICROWAVE SYSTEMS

Scientific and Technical Volga region Bulletin ◽

10.24153/2079-5920-2018-8-5-102-104 ◽

2018 ◽

Vol 8 (5) ◽

pp. 102-104

Author(s):

I.I. Batyirshin ◽

◽

O.G. Morozov ◽

A.A. Ivanov ◽

A.J. Sakhabutdinov ◽

...

Keyword(s):

Measurement Errors ◽

Errors Analysis

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Quantifying the Stability of Coupled Genetic and Epigenetic Switches With Variational Methods

Frontiers in Genetics ◽

10.3389/fgene.2020.636724 ◽

2021 ◽

Vol 11 ◽

Author(s):

Amogh Sood ◽

Bin Zhang

Keyword(s):

Gene Regulation ◽

Transcription Factors ◽

Cell Fate ◽

Histone Modifications ◽

Regulatory Networks ◽

Variational Principles ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Cell Fate Decisions ◽

The Impact

The Waddington landscape provides an intuitive metaphor to view development as a ball rolling down the hill, with distinct phenotypes as basins and differentiation pathways as valleys. Since, at a molecular level, cell differentiation arises from interactions among the genes, a mathematical definition for the Waddington landscape can, in principle, be obtained by studying the gene regulatory networks. For eukaryotes, gene regulation is inextricably and intimately linked to histone modifications. However, the impact of such modifications on both landscape topography and stability of attractor states is not fully understood. In this work, we introduced a minimal kinetic model for gene regulation that combines the impact of both histone modifications and transcription factors. We further developed an approximation scheme based on variational principles to solve the corresponding master equation in a second quantized framework. By analyzing the steady-state solutions at various parameter regimes, we found that histone modification kinetics can significantly alter the behavior of a genetic network, resulting in qualitative changes in gene expression profiles. The emerging epigenetic landscape captures the delicate interplay between transcription factors and histone modifications in driving cell-fate decisions.

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Nearby transposable elements impact plant stress gene regulatory networks: a meta-analysis in A. thaliana and S. lycopersicum

BMC Genomics ◽

10.1186/s12864-021-08215-8 ◽

2022 ◽

Vol 23 (1) ◽

Author(s):

Jan Deneweth ◽

Yves Van de Peer ◽

Vanessa Vermeirssen

Keyword(s):

Gene Regulation ◽

Transposable Elements ◽

Regulatory Networks ◽

Expression Profiles ◽

Meta Analysis ◽

Light Stress ◽

Plant Stress ◽

Stress Conditions ◽

Specific Gene ◽

Regulatory Motifs

Abstract Background Transposable elements (TE) make up a large portion of many plant genomes and are playing innovative roles in genome evolution. Several TEs can contribute to gene regulation by influencing expression of nearby genes as stress-responsive regulatory motifs. To delineate TE-mediated plant stress regulatory networks, we took a 2-step computational approach consisting of identifying TEs in the proximity of stress-responsive genes, followed by searching for cis-regulatory motifs in these TE sequences and linking them to known regulatory factors. Through a systematic meta-analysis of RNA-seq expression profiles and genome annotations, we investigated the relation between the presence of TE superfamilies upstream, downstream or within introns of nearby genes and the differential expression of these genes in various stress conditions in the TE-poor Arabidopsis thaliana and the TE-rich Solanum lycopersicum. Results We found that stress conditions frequently expressed genes having members of various TE superfamilies in their genomic proximity, such as SINE upon proteotoxic stress and Copia and Gypsy upon heat stress in A. thaliana, and EPRV and hAT upon infection, and Harbinger, LINE and Retrotransposon upon light stress in S. lycopersicum. These stress-specific gene-proximal TEs were mostly located within introns and more detected near upregulated than downregulated genes. Similar stress conditions were often related to the same TE superfamily. Additionally, we detected both novel and known motifs in the sequences of those TEs pointing to regulatory cooption of these TEs upon stress. Next, we constructed the regulatory network of TFs that act through binding these TEs to their target genes upon stress and discovered TE-mediated regulons targeted by TFs such as BRB/BPC, HD, HSF, GATA, NAC, DREB/CBF and MYB factors in Arabidopsis and AP2/ERF/B3, NAC, NF-Y, MYB, CXC and HD factors in tomato. Conclusions Overall, we map TE-mediated plant stress regulatory networks using numerous stress expression profile studies for two contrasting plant species to study the regulatory role TEs play in the response to stress. As TE-mediated gene regulation allows plants to adapt more rapidly to new environmental conditions, this study contributes to the future development of climate-resilient plants.

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The use of numerical methods in the design of a formula that returns the surface of the leaves of Phragmites australis (Cav.) Trin. Ex Steud.

Limnological Review ◽

10.2478/limre-2020-0004 ◽

2020 ◽

Vol 20 (1) ◽

pp. 33-39

Author(s):

Katarzyna Krzyżanowska ◽

Paweł Krzyżanowski

Keyword(s):

Linear Regression ◽

Phragmites Australis ◽

Measurement Errors ◽

Numerical Models ◽

Common Reed ◽

Small Samples ◽

Real Surface ◽

Maximum Width ◽

Average Accuracy ◽

Leaf Dimensions

AbstractThe paper presents the results of calculations and a verification of numerical models developed for estimating the surface of leaves of the common reed (Phragmites australis (Cav.) Trin. Ex Steud.). The research sample consisted of 137 leaves collected from the rush zone of Lake Raduńskie Górne in 2018. The total area of leaves obtained for testing was 1932.3 cm2. To derive a formula that returns the surface of common reed foliage regression models were used – MLR (Multiple Linear Regression) and SLR (Stepwise Linear Regression). It has been shown that the measurement of basic leaf dimensions (i.e. length – L, mid-width – WM and maximum width – WX) makes it possible to define an empirical formula which, with an average accuracy of 99.9%, allows the real surface of leaves to be estimated. The modelling results were compared with formulas currently used in practice, and the measurement errors were determined using these formulas. It has been shown that the formulas used to date are subject to RMSE to the value of 1.19-2.52. The application of the developed formula (A = 0.4486 – 0.046 L + 7.9267 WM – 5.8121 WX + 0.5853 L • WX) will significantly reduce errors in leaf surface estimation (RMSE = 0.86) and thus the amount of reed transpiration and evapotranspiration, especially in the case of handling small samples (number of leaves and measurements).

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Expression profiles of sugarcane under drought conditions: Variation in gene regulation

Genetics and Molecular Biology ◽

10.1590/s1415-475738420140288 ◽

2015 ◽

Vol 38 (4) ◽

pp. 465-469 ◽

Cited By ~ 6

Author(s):

Júlio César Farias de Andrade ◽

Jackeline Terto ◽

José Vieira Silva ◽

Cícero Almeida

Keyword(s):

Gene Regulation ◽

Expression Profiles ◽

Drought Conditions

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