scholarly journals Single-cell RNA-seq reveals distinct injury responses in different types of DRG sensory neurons

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Ganlu Hu ◽  
Kevin Huang ◽  
Youjin Hu ◽  
Guizhen Du ◽  
Zhigang Xue ◽  
...  
Keyword(s):  
Single Cell ◽  
Sensory Neurons ◽  
Rna Seq ◽  
Different Types

scholarly journals Hierarchical deconstruction of mouse olfactory sensory neurons: from whole mucosa to single-cell RNA-seq

2015 ◽  
Vol 5 (1) ◽  
Author(s):  
Luis R. Saraiva ◽  
Ximena Ibarra-Soria ◽  
Mona Khan ◽  
Masayo Omura ◽  
Antonio Scialdone ◽  
...  
Keyword(s):  
Single Cell ◽  
Sensory Neurons ◽  
Olfactory Sensory Neurons ◽  
Rna Seq

scholarly journals Single-cell RNA seq analysis identifies the biomarkers and differentiation of chondrocyte in human osteoarthritis

2020 ◽  
Author(s):  
Xiaolu Zhang ◽  
Nianlai Huang ◽  
Rongfu Huang ◽  
Liangming Wang ◽  
Qingfeng Ke ◽  
...  
Keyword(s):  
Single Cell ◽  
Differential Expression ◽  
Cell Subset ◽  
Marker Genes ◽  
Rna Seq ◽  
Candidate Marker ◽  
Protein Protein Interaction ◽  
Kegg Analysis ◽  
Hypertrophic Chondrocyte ◽  
Different Types

Abstract Background： Single-cell RNA sequencing (scRNA-seq) was recently adopted for exploring molecular programmes and lineage progression patterns of pathogenesis of important diseases. In this study, scRNA-seq was used to identify potential markers for chondrocytes in osteoarthritis (OA) and to explore the function of different types of chondrocytes in OA.Methods：Here we aimed to identify the biomarkers and differentiation of chondrocyte by Single-cell RNA seq analysis. GeneOntology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were used to identify the function of candidate marker genes in chondrocytes. Protein–protein interaction (PPI) network was constructed to find the hub genes in 3 types of chondrocyte respectively. We also used qRT-PCR to detect the expression level of the candidate marker genes in different types of chondrocyte. Results： In this study, we characterized the single-cell expression profiling of 480 chondrocyte samples and found hypertrophic chondrocyte (HTC), homeostatic chondrocyte (HomC) and fibrocartilage chondrocyte (FC) respectively. The results of GO and KEGG analysis showed the candidate marker genes made specific function in these chondrocytes to regulate the development of OAs respectively. We further revealed the differential expression of top 10 marker genes in 3 types of chondrocyte. The marker genes of HTC and FC were mainly expressed in their cell subset respectively. The marker genes of HomC did not have obviously differential expression among different types of chondrocyte. Last, we predicted the key genes in each cell subset. CD44, JUN and FN1 were predicted tightly related to the proliferation and differentiation of chondrocytes in OAs and could be regarded as biomarkers to estimate the development of OA. Conclusion： Our results provide new insights into exploring the roles of different types of chondrocyte in OA. The biomarkers of chondrocyte were also valuable for estimating OA progression.

scholarly journals Integrative analysis of single cell genomics data by coupled nonnegative matrix factorizations

2018 ◽  
Author(s):  
Zhana Duren ◽  
Xi Chen ◽  
Mahdi Zamanighomi ◽  
Wanwen Zeng ◽  
Ansuman T Satpathy ◽  
...  
Keyword(s):  
Single Cell ◽  
Nonnegative Matrix ◽  
Integrative Analysis ◽  
Matrix Factorizations ◽  
Joint Analysis ◽  
Rna Seq ◽  
Single Cell Genomics ◽  
Clustering Problem ◽  
Two Samples ◽  
Different Types

AbstractWhen different types of functional genomics data are generated on single cells from different samples of cells from the same heterogeneous population, the clustering of cells in the different samples should be coupled. We formulate this “coupled clustering” problem as an optimization problem, and propose the method of coupled nonnegative matrix factorizations (coupled NMF) for its solution. The method is illustrated by the integrative analysis of single cell RNA-seq and single cell ATAC-seq data.Significance StatementsBiological samples are often heterogeneous mixtures of different types of cells. Suppose we have two single cell data sets, each providing information on a different cellular feature and generated on a different sample from this mixture. Then, the clustering of cells in the two samples should be coupled as both clusterings are reflecting the underlying cell types in the same mixture. This “coupled clustering” problem is a new problem not covered by existing clustering methods. In this paper we develop an approach for its solution based the coupling of two nonnegative matrix factorizations. The method should be useful for integrative single cell genomics analysis tasks such as the joint analysis of single cell RNA-seq and single cell ATAC-seq data.

scholarly journals Single-cell RNA seq analysis identifies the biomarkers and differentiation of chondrocyte in human osteoarthritis

2020 ◽  
Author(s):  
Xiaolu Zhang ◽  
Nianlai Huang ◽  
Rongfu Huang ◽  
Liangming Wang ◽  
Qingfeng Ke ◽  
...  
Keyword(s):  
Single Cell ◽  
Differential Expression ◽  
Cell Subset ◽  
Marker Genes ◽  
Rna Seq ◽  
Candidate Marker ◽  
Protein Protein Interaction ◽  
Kegg Analysis ◽  
Hypertrophic Chondrocyte ◽  
Different Types

Abstract Background： Single-cell RNA sequencing (scRNA-seq) was recently adopted for exploring molecular programmes and lineage progression patterns of pathogenesis of important diseases. In this study, we use scRNA-seq to identify potential markers for chondrocytes in osteoarthritis (OA) and explore the function of different types of chondrocytes in OA. Methods：Here we aimed to identifies the biomarkers and differentiation of chondrocyte by Single-cell RNA seq analysis. GO and KEGG analysis were used to prove the function of candidate marker genes in chondrocytes. Protein–protein interaction (PPI) network was constructed to found the hub genes in 3 types of chondrocyte respectively. We also used qRT-PCR to detect the expression level of the candidate marker genes in different types of chondrocyte. Results： In this study, we characterized the single-cell expression profiling of 480 chondrocyte samples and found hypertrophic chondrocyte (HTC), homeostatic chondrocyte (HomC) and fibrocartilage chondrocyte (FC) respectively. The results of GO and KEGG analysis to the candidate marker genes of 3 types of chondrocyte. showed the candidate marker genes made specific function in these chondrocytes to regulate the development of OAs respectively. We further revealed the differential expression of top 10 marker genes of 3 types of chondrocyte in different type of chondrocytes. The marker genes of HTC and FC were mainly expressed in their respective cell. The marker genes of HomC did not have obviously differential expression among different types of chondrocyte. Last, we proved the key genes in each cell subset. CD44, JUN and FN1 were proved tightly related to the proliferation and differentiation of chondrocytes in OAs and could be regarded as biomarkers to estimate the development of OA. Conclusion： Our results provide new insights into exploring the roles of different types of chondrocyte in OA. The biomarkers of chondrocyte were also valuable for estimating OA progression.

scholarly journals Transcriptome Analysis of Murine Olfactory Sensory Neurons during Development Using Single Cell RNA-Seq

2016 ◽  
Vol 41 (4) ◽  
pp. 313-323 ◽  
Author(s):  
Paul Scholz ◽  
Benjamin Kalbe ◽  
Fabian Jansen ◽  
Janine Altmueller ◽  
Christian Becker ◽  
...  
Keyword(s):  
Single Cell ◽  
Sensory Neurons ◽  
Transcriptome Analysis ◽  
Olfactory Sensory Neurons ◽  
Rna Seq

scholarly journals Single-cell RNA seq analysis identifies the biomarkers and differentiation of chondrocyte in human osteoarthritis

2020 ◽  
Author(s):  
Xiaolu Zhang ◽  
Nianlai Huang ◽  
Rongfu Huang ◽  
Liangming Wang ◽  
Qingfeng Ke ◽  
...  
Keyword(s):  
Single Cell ◽  
Differential Expression ◽  
Cell Subset ◽  
Marker Genes ◽  
Rna Seq ◽  
Candidate Marker ◽  
Protein Protein Interaction ◽  
Kegg Analysis ◽  
Hypertrophic Chondrocyte ◽  
Different Types

Abstract Background: Single-cell RNA sequencing (scRNA-seq) was recently adopted for exploring molecular programmes and lineage progression patterns of pathogenesis of important diseases. In this study, scRNA-seq was used to identify potential markers for chondrocytes in osteoarthritis (OA) and to explore the function of different types of chondrocytes in OA. Methods: Here we aimed to identify the biomarkers and differentiation of chondrocyte by Single-cell RNA seq analysis. GeneOntology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were used to identify the function of candidate marker genes in chondrocytes. Protein-protein interaction (PPI) network was constructed to find the hub genes in 3 types of chondrocyte respectively. We also used qRT-PCR to detect the expression level of the candidate marker genes in different types of chondrocyte. Results: In this study, we characterized the single-cell expression profiling of 480 chondrocyte samples and found hypertrophic chondrocyte (HTC), homeostatic chondrocyte (HomC) and fibrocartilage chondrocyte (FC) respectively. The results of GO and KEGG analysis showed the candidate marker genes made specific function in these chondrocytes to regulate the development of OAs respectively. We further revealed the differential expression of top 10 marker genes in 3 types of chondrocyte. The marker genes of HTC and FC were mainly expressed in their cell subset respectively. The marker genes of HomC did not have obviously differential expression among different types of chondrocyte. Last, we predicted the key genes in each cell subset. CD44, JUN and FN1 were predicted tightly related to the proliferation and differentiation of chondrocytes in OAs and could be regarded as biomarkers to estimate the development of OA. Conclusion: Our results provide new insights into exploring the roles of different types of chondrocyte in OA. The biomarkers of chondrocyte were also valuable for estimating OA progression.

scholarly journals Integrative analysis of single-cell genomics data by coupled nonnegative matrix factorizations

2018 ◽  
Vol 115 (30) ◽  
pp. 7723-7728 ◽  
Author(s):  
Zhana Duren ◽  
Xi Chen ◽  
Mahdi Zamanighomi ◽  
Wanwen Zeng ◽  
Ansuman T. Satpathy ◽  
...  
Keyword(s):  
Single Cell ◽  
Optimization Problem ◽  
Single Cells ◽  
Nonnegative Matrix ◽  
Heterogeneous Population ◽  
Integrative Analysis ◽  
Matrix Factorizations ◽  
Rna Seq ◽  
Clustering Problem ◽  
Different Types

When different types of functional genomics data are generated on single cells from different samples of cells from the same heterogeneous population, the clustering of cells in the different samples should be coupled. We formulate this “coupled clustering” problem as an optimization problem and propose the method of coupled nonnegative matrix factorizations (coupled NMF) for its solution. The method is illustrated by the integrative analysis of single-cell RNA-sequencing (RNA-seq) and single-cell ATAC-sequencing (ATAC-seq) data.

Sign in / Sign up

Export Citation Format

Share Document