scholarly journals Microfluidic single-cell real-time PCR for comparative analysis of gene expression patterns

2012 ◽  
Vol 7 (5) ◽  
pp. 829-838 ◽  
Author(s):  
Veronica Sanchez-Freire ◽  
Antje D Ebert ◽  
Tomer Kalisky ◽  
Stephen R Quake ◽  
Joseph C Wu
Keyword(s):  
Gene Expression ◽  
Comparative Analysis ◽  
Single Cell ◽  
Real Time ◽  
Real Time Pcr ◽  
Expression Patterns ◽  
Gene Expression Patterns

scholarly journals Gene expression patterns in bone following lipopolysaccharide stimulation

2014 ◽  
Vol 19 (4) ◽  
Author(s):  
Jing Yang ◽  
Nan Su ◽  
Xiaolan Du ◽  
Lin Chen
Keyword(s):  
Gene Expression ◽  
Bone Formation ◽  
Real Time ◽  
Real Time Pcr ◽  
Early Stage ◽  
System Development ◽  
Expression Patterns ◽  
Osteoclast Differentiation ◽  
Gene Expression Patterns ◽  
Expression Levels

AbstractBone displays suppressed osteogenesis in inflammatory diseases such as sepsis and rheumatoid arthritis. However, the underlying mechanisms have not yet been clearly explained. To identify the gene expression patterns in the bone, we performed Affymetrix Mouse Genome 430 2.0 Array with RNA isolated from mouse femurs 4 h after lipopolysaccharide (LPS) administration. The gene expressions were confirmed with real-time PCR. The serum concentration of the N-terminal propeptide of type I collagen (PINP), a bone-formation marker, was determined using ELISA. A total of 1003 transcripts were upregulated and 159 transcripts were downregulated (more than twofold upregulation or downregulation). Increased expression levels of the inflammation-related genes interleukin-6 (IL-6), interleukin-1β (IL-1β) and tumor necrosis factor α (TNF-α) were confirmed from in the period 4 h to 72 h after LPS administration using real-time PCR. Gene ontogene analysis found four bone-related categories involved in four biological processes: system development, osteoclast differentiation, ossification and bone development. These processes involved 25 upregulated genes. In the KEGG database, we further analyzed the transforming growth factor β (TGF-β) pathway, which is strongly related to osteogenesis. The upregulated bone morphogenetic protein 2 (BMP2) and downregulated inhibitor of DNA binding 4 (Id4) expressions were further confirmed by real-time PCR after LPS stimulation. The osteoblast function was determined through examination of the expression levels of core binding factor 1 (Cbfa1) and osteocalcin (OC) in bone tissues and serum PINP from 4 h to 72 h after LPS administration. The expressions of OC and Cbfa1 decreased 6 h after administration (p < 0.05). Significantly suppressed PINP levels were observed in the later stage (from 8 h to 72 h, p < 0.05) but not in the early stage (4 h or 6 h, p > 0.05) of LPS stimulation. The results of this study suggest that LPS induces elevated expressions of skeletal system development- and osteoclast differentiation-related genes and inflammation genes at an early stage in the bone. The perturbed functions of these two groups of genes may lead to a faint change in osteogenesis at an early stage of LPS stimulation. Suppressed bone formation was found at later stages in response to LPS stimulation.

Gene expression patterns for GDNF and its receptors in the human putamen affected by Parkinson's disease: A real-time PCR study

2006 ◽  
Vol 252 (1-2) ◽  
pp. 160-166 ◽  
Author(s):  
Cristina M. Bäckman ◽  
Lufei Shan ◽  
Ya Jun Zhang ◽  
Barry J. Hoffer ◽  
Sherry Leonard ◽  
...  
Keyword(s):  
Gene Expression ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Real Time ◽  
Real Time Pcr ◽  
Expression Patterns ◽  
Gene Expression Patterns

scholarly journals Cryopreservation of microglia enables single-cell RNA sequencing with minimal effects on disease-related gene expression patterns

iScience ◽  
2021 ◽  
Vol 24 (4) ◽  
pp. 102357
Author(s):  
Brenda Morsey ◽  
Meng Niu ◽  
Shetty Ravi Dyavar ◽  
Courtney V. Fletcher ◽  
Benjamin G. Lamberty ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Rna Sequencing ◽  
Expression Patterns ◽  
Gene Expression Patterns ◽  
Related Gene ◽  
Single Cell Rna Sequencing ◽  
Disease Related Gene

scholarly journals ZipSeq : Barcoding for Real-time Mapping of Single Cell Transcriptomes

2020 ◽  
Author(s):  
Kenneth H. Hu ◽  
John P. Eichorst ◽  
Chris S. McGinnis ◽  
David M. Patterson ◽  
Eric D. Chow ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Real Time ◽  
Dimensional Space ◽  
Single Cells ◽  
Expression Patterns ◽  
Live Cells ◽  
Glass Substrates ◽  
Complete Mapping

ABSTRACTSpatial transcriptomics seeks to integrate single-cell transcriptomic data within the 3-dimensional space of multicellular biology. Current methods use glass substrates pre-seeded with matrices of barcodes or fluorescence hybridization of a limited number of probes. We developed an alternative approach, called ‘ZipSeq’, that uses patterned illumination and photocaged oligonucleotides to serially print barcodes (Zipcodes) onto live cells within intact tissues, in real-time and with on-the-fly selection of patterns. Using ZipSeq, we mapped gene expression in three settings: in-vitro wound healing, live lymph node sections and in a live tumor microenvironment (TME). In all cases, we discovered new gene expression patterns associated with histological structures. In the TME, this demonstrated a trajectory of myeloid and T cell differentiation, from periphery inward. A variation of ZipSeq efficiently scales to the level of single cells, providing a pathway for complete mapping of live tissues, subsequent to real-time imaging or perturbation.

scholarly journals Single-cell gene expression patterns in lupus monocytes independently indicate disease activity, interferon and therapy

2017 ◽  
Vol 4 (1) ◽  
pp. e000202 ◽  
Author(s):  
Zhongbo Jin ◽  
Wei Fan ◽  
Mark A Jensen ◽  
Jessica M Dorschner ◽  
George F Bonadurer ◽  
...  
Keyword(s):  
Gene Expression ◽  
Disease Activity ◽  
Single Cell ◽  
Expression Patterns ◽  
Gene Expression Patterns ◽  
Cell Gene Expression ◽  
Cell Gene

scholarly journals A single cell brain atlas in human Alzheimer’s disease

2019 ◽  
Author(s):  
Alexandra Grubman ◽  
Gabriel Chew ◽  
John F. Ouyang ◽  
Guizhi Sun ◽  
Xin Yi Choo ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcription Factor ◽  
Single Cell ◽  
Cell Fate ◽  
Expression Patterns ◽  
Cell Types ◽  
Gene Expression Patterns ◽  
Cell Type ◽  
Web Resource ◽  
Cell Type Specific

AbstractAlzheimer’s disease (AD) is a heterogeneous disease that is largely dependent on the complex cellular microenvironment in the brain. This complexity impedes our understanding of how individual cell types contribute to disease progression and outcome. To characterize the molecular and functional cell diversity in the human AD brain we utilized single nuclei RNA- seq in AD and control patient brains in order to map the landscape of cellular heterogeneity in AD. We detail gene expression changes at the level of cells and cell subclusters, highlighting specific cellular contributions to global gene expression patterns between control and Alzheimer’s patient brains. We observed distinct cellular regulation of APOE which was repressed in oligodendrocyte progenitor cells (OPCs) and astrocyte AD subclusters, and highly enriched in a microglial AD subcluster. In addition, oligodendrocyte and microglia AD subclusters show discordant expression of APOE. Integration of transcription factor regulatory modules with downstream GWAS gene targets revealed subcluster-specific control of AD cell fate transitions. For example, this analysis uncovered that astrocyte diversity in AD was under the control of transcription factor EB (TFEB), a master regulator of lysosomal function and which initiated a regulatory cascade containing multiple AD GWAS genes. These results establish functional links between specific cellular sub-populations in AD, and provide new insights into the coordinated control of AD GWAS genes and their cell-type specific contribution to disease susceptibility. Finally, we created an interactive reference web resource which will facilitate brain and AD researchers to explore the molecular architecture of subtype and AD-specific cell identity, molecular and functional diversity at the single cell level.HighlightsWe generated the first human single cell transcriptome in AD patient brainsOur study unveiled 9 clusters of cell-type specific and common gene expression patterns between control and AD brains, including clusters of genes that present properties of different cell types (i.e. astrocytes and oligodendrocytes)Our analyses also uncovered functionally specialized sub-cellular clusters: 5 microglial clusters, 8 astrocyte clusters, 6 neuronal clusters, 6 oligodendrocyte clusters, 4 OPC and 2 endothelial clusters, each enriched for specific ontological gene categoriesOur analyses found manifold AD GWAS genes specifically associated with one cell-type, and sets of AD GWAS genes co-ordinately and differentially regulated between different brain cell-types in AD sub-cellular clustersWe mapped the regulatory landscape driving transcriptional changes in AD brain, and identified transcription factor networks which we predict to control cell fate transitions between control and AD sub-cellular clustersFinally, we provide an interactive web-resource that allows the user to further visualise and interrogate our dataset.Data resource web interface:http://adsn.ddnetbio.com

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