scholarly journals C. elegansexhibits coordinated oscillation in gene activation in single-cell developmental data

2017 ◽  
Author(s):  
Luke A.D. Hutchison ◽  
Bonnie Berger ◽  
Isaac Kohane
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Meta Analysis ◽  
Gene Activation ◽  
Developmental Genes ◽  
Division Rate ◽  
Developmental Processes ◽  
Anatomy Ontology ◽  
Analysis Techniques ◽  
Cell Phenotypes

AbstractBackgroundThe advent ofin vivoautomated single-cell lineaging and sequencing will dramatically increase our understanding of development. New integrative analysis techniques are needed to generate insights from single-cell developmental data.ResultsWe applied novel meta-analysis techniques to the EPIC single-cell-resolution developmental gene expression dataset forC. elegansto show that a simple linear combination of the expression levels of the developmental genes is strongly correlated with the developmental age of the organism, irrespective of the cell division rate of different cell lineages. We uncovered a pattern of collective sinusoidal oscillation in gene activation, in multiple dominant frequencies and in multiple orthogonal axes of gene expression, pointing to the existence of a coordinated, multi-frequency global timing mechanism. We developed a novel method based on Fisher’s Discriminant Analysis (FDA) to identify linear gene expression weightings that are able to produce sinusoidal oscillations of any frequency and phase, adding to the evidence that oscillatory mechanisms likely play an important role in the timing of development. We cross-linked EPIC with gene ontology and anatomy ontology terms, employing FDA methods to identify previously unknown positive and negative genetic contributions to developmental processes and cell phenotypes.ConclusionsThis meta-analysis demonstrates new evidence for direct linear and/or sinusoidal mechanisms regulating the timing of development. We uncovered a number of previously unknown positive and negative correlations between developmental genes and developmental processes or cell phenotypes. The presented novel analysis techniques are broadly applicable within developmental biology.

scholarly journals Meta-analysis of Caenorhabditis elegans single-cell developmental data reveals multi-frequency oscillation in gene activation

2019 ◽  
Vol 36 (13) ◽  
pp. 4047-4057 ◽  
Author(s):  
Luke A D Hutchison ◽  
Bonnie Berger ◽  
Isaac S Kohane
Keyword(s):  
Gene Expression ◽  
Caenorhabditis Elegans ◽  
Discriminant Analysis ◽  
Single Cell ◽  
Meta Analysis ◽  
Gene Activation ◽  
Developmental Genes ◽  
Fisher’S Discriminant Analysis ◽  
Visualization Techniques ◽  
Cell Phenotypes

Abstract Motivation The advent of in vivo automated techniques for single-cell lineaging, sequencing and analysis of gene expression has begun to dramatically increase our understanding of organismal development. We applied novel meta-analysis and visualization techniques to the EPIC single-cell-resolution developmental gene expression dataset for Caenorhabditis elegans from Bao, Murray, Waterston et al. to gain insights into regulatory mechanisms governing the timing of development. Results Our meta-analysis of the EPIC dataset revealed that a simple linear combination of the expression levels of the developmental genes is strongly correlated with the developmental age of the organism, irrespective of the cell division rate of different cell lineages. We uncovered a pattern of collective sinusoidal oscillation in gene activation, in multiple dominant frequencies and in multiple orthogonal axes of gene expression, pointing to the existence of a coordinated, multi-frequency global timing mechanism. We developed a novel method based on Fisher’s Discriminant Analysis to identify gene expression weightings that maximally separate traits of interest, and found that remarkably, simple linear gene expression weightings are capable of producing sinusoidal oscillations of any frequency and phase, adding to the growing body of evidence that oscillatory mechanisms likely play an important role in the timing of development. We cross-linked EPIC with gene ontology and anatomy ontology terms, employing Fisher’s Discriminant Analysis methods to identify previously unknown positive and negative genetic contributions to developmental processes and cell phenotypes. This meta-analysis demonstrates new evidence for direct linear and/or sinusoidal mechanisms regulating the timing of development. We uncovered a number of previously unknown positive and negative correlations between developmental genes and developmental processes or cell phenotypes. Our results highlight both the continued relevance of the EPIC technique, and the value of meta-analysis of previously published results. The presented analysis and visualization techniques are broadly applicable across developmental and systems biology. Availability and implementation Analysis software available upon request. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Single-cell gene expression reveals a landscape of regulatory T cell phenotypes shaped by the TCR

2018 ◽  
Vol 19 (3) ◽  
pp. 291-301 ◽  
Author(s):  
David Zemmour ◽  
Rapolas Zilionis ◽  
Evgeny Kiner ◽  
Allon M. Klein ◽  
Diane Mathis ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cell ◽  
Single Cell ◽  
Regulatory T Cell ◽  
Cell Gene Expression ◽  
T Cell Phenotypes ◽  
Cell Phenotypes ◽  
Cell Gene

scholarly journals Publisher Correction: Single-cell gene expression reveals a landscape of regulatory T cell phenotypes shaped by the TCR

2018 ◽  
Vol 19 (6) ◽  
pp. 645-645 ◽  
Author(s):  
David Zemmour ◽  
Rapolas Zilionis ◽  
Evgeny Kiner ◽  
Allon M Klein ◽  
Diane Mathis ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cell ◽  
Single Cell ◽  
Regulatory T Cell ◽  
Cell Gene Expression ◽  
T Cell Phenotypes ◽  
Cell Phenotypes ◽  
Cell Gene

74 Novel approach for profiling immune-tumor cell interactions and mutations in the same tumor section by multiplex immunohistochemistry and NGS in immuno-oncology trials

2020 ◽  
Vol 8 (Suppl 3) ◽  
pp. A80-A80
Author(s):  
Nathan Riccitelli ◽  
Jennifer Bordeaux ◽  
Nancy Valencia ◽  
Ju Young Kim ◽  
Sarah Johnson ◽  
...  
Keyword(s):  
Gene Expression ◽  
Clinical Trials ◽  
Nucleic Acid ◽  
Nucleic Acids ◽  
Clinical Response ◽  
Tumor Tissue ◽  
Immune Cell ◽  
Meta Analysis ◽  
Novel Approach ◽  
Cell Phenotypes

BackgroundBoth proteins (e.g., PD-L1 IHC) and tumor mutation burden (NGS-based) are known to independently predict clinical response to anti-PD-1/PD-L1 therapies. In a meta-analysis of tumor specimens from 8135 patients treated with PD-1/PD-L1 blockers, multiplex fluorescence immunohistochemistry (mFIHC) had significantly higher diagnostic accuracy than PD-L1 IHC, tumor mutational burden (TMB), or gene expression profiling alone in predicting clinical response1 or equivalent to a multimodality approach (e.g., PD-L1IHC + TMB). While the benefits of combining mFIHC (tumor-immune interplay) and NGS approaches in selection of patients for next generation immunotherapies is appealing, tumor tissue is a key limiting factor for multimodality analyses in clinical trials. To address this critical limitation, we developed a novel approach for sequential profiling of tumor and immune cell interactions by 7-parameter mFIHC assays, followed by analyses of nucleic acid extracted from same tissue sections.MethodsFormalin-fixed paraffin-embedded (FFPE) tumor tissue and cell line blocks were sectioned, and then stained using mFIHC followed by isolation of nucleic acids, or direct isolation of total nucleic acids. NanoString, qPCR, and NGS were performed on isolated nucleic acids. Nucleic acid quality, transcript abundance, and TMB scores were compared before and after mFIHC staining.Results mFIHC revealed a broad range of immune cell phenotypes and spatial interactions, including T cells, B cells, NK cells, monocytes, neutrophils, and their functional status. Isolation of testable quantities of DNA from mFIHC treated slides was achieved when using a DNA-only isolation method, and TMB scores were robust across tested conditions. Cell phenotypes identified by mFIHC were compared to TMB scores across the tested samples. Following mFIHC treatment, RNA yields were reduced relative to the non-mFIHC treated replicates, but still sufficient for optimal input into a 770-target NanoString gene expression panel. However, for mFIHC treated samples, transcript levels were not distinguishable from background for the assessed targets.ConclusionsIn summary, integrating mFIHC testing and TMB analysis on the same samples allows for comprehensive biomarker evaluation. The real world benefits of the combined approach will be described in upcoming clinical trials.ReferenceLu, et al., Comparison of biomarker modalities for predicting response to PD-1/PD-L1 checkpoint blockade, a systematic review and meta-analysis. JAMA Oncology 2019; 5(8):1195–1204

scholarly journals Single cell gene expression profiling of nasal ciliated cells reveals distinctive biological processes related to epigenetic mechanisms in patients with severe COVID-19

2021 ◽  
Author(s):  
Luis Diambra ◽  
Andres M Alonso ◽  
Silvia Sookoian ◽  
Carlos Pirola
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Gene Activation ◽  
Healthy Controls ◽  
Epigenetic Mechanisms ◽  
Ciliated Cells ◽  
Moderate Disease ◽  
Cell Gene Expression

Objective: To explore the molecular processes associated with cellular regulatory programs in patients with COVID-19, including gene activation or repression mediated by epigenetic mechanisms. We hypothesized that a comprehensive gene expression profiling of nasopharyngeal epithelial cells might expand understanding of the pathogenic mechanisms of severe COVID-19. Methods: We used single-cell RNA sequencing (scRNAseq) profiling of ciliated cells (n = 12725) from healthy controls (SARS-CoV-2 negative n =13) and patients with mild/moderate (n =13) and severe (n =14) COVID-19. ScRNAseq data at the patient level were used to perform gene set and pathway enrichment analyses. We prioritized candidate miRNA-target interactions and epigenetic mechanisms. Results: Pathways linked to mitochondrial function, misfolded proteins, and membrane permeability were upregulated in patients with mild/moderate disease compared to healthy controls. Besides, we noted that compared to mild/moderate disease, cells derived from severe COVID-19 patients had downregulation of sub-networks associated with epigenetic mechanisms, including DNA and histone H3K4 methylation and chromatin remodeling regulation. We found 11-ranked miRNAs that may explain miRNA-dependent regulation of histone methylation, some of which share seed sequences with SARS-CoV-2 miRNAs. Conclusion: Our results may provide novel insights into the epigenetic mechanisms mediating the clinical course of SARS-CoV-2 infection.

scholarly journals The BMP signaling gradient is interpreted through concentration thresholds in dorsal–ventral axial patterning

PLoS Biology ◽  
2021 ◽  
Vol 19 (1) ◽  
pp. e3001059
Author(s):  
Hannah Greenfeld ◽  
Jerome Lin ◽  
Mary C. Mullins
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Target Gene ◽  
Target Genes ◽  
Gene Activation ◽  
Spatial Relationship ◽  
Bmp Signaling ◽  
Target Gene Expression ◽  
Gradient Slope ◽  
Distinct Cell

Bone Morphogenetic Protein (BMP) patterns the dorsal–ventral (DV) embryonic axis in all vertebrates, but it is unknown how cells along the DV axis interpret and translate the gradient of BMP signaling into differential gene activation that will give rise to distinct cell fates. To determine the mechanism of BMP morphogen interpretation in the zebrafish gastrula, we identified 57 genes that are directly activated by BMP signaling. By using Seurat analysis of single-cell RNA sequencing (scRNA-seq) data, we found that these genes are expressed in at least 3 distinct DV domains of the embryo. We distinguished between 3 models of BMP signal interpretation in which cells activate distinct gene expression through interpretation of thresholds of (1) the BMP signaling gradient slope; (2) the BMP signal duration; or (3) the level of BMP signal activation. We tested these 3 models using quantitative measurements of phosphorylated Smad5 (pSmad5) and by examining the spatial relationship between BMP signaling and activation of different target genes at single-cell resolution across the embryo. We found that BMP signaling gradient slope or BMP exposure duration did not account for the differential target gene expression domains. Instead, we show that cells respond to 3 distinct levels of BMP signaling activity to activate and position target gene expression. Together, we demonstrate that distinct pSmad5 threshold levels activate spatially distinct target genes to pattern the DV axis.

Sign in / Sign up

Export Citation Format

Share Document