An Informative Approach to Single-Cell Sequencing Analysis

2019 ◽  
pp. 81-96
Author(s):  
Yukie Kashima ◽  
Ayako Suzuki ◽  
Yutaka Suzuki
Keyword(s):  
Single Cell ◽  
Sequencing Analysis ◽  
Single Cell Sequencing ◽  
Informative Approach

scholarly journals Tracking the important role of JUNB in hepatocellular carcinoma by single‑cell sequencing analysis

2019 ◽  
Author(s):  
Peng Yan ◽  
Bin Zhou ◽  
Yingdong Ma ◽  
Ani Wang ◽  
Xiaojun Hu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Single Cell ◽  
Sequencing Analysis ◽  
Single Cell Sequencing

scholarly journals Using single-cell sequencing technology to detect circulating tumor cells in solid tumors

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Jiasheng Xu ◽  
Kaili Liao ◽  
Xi Yang ◽  
Chengfeng Wu ◽  
Wei Wu ◽  
...  
Keyword(s):  
Single Cell ◽  
Solid Tumors ◽  
Tumor Cells ◽  
Circulating Tumor Cells ◽  
Peripheral Blood ◽  
High Throughput Sequencing ◽  
Metastatic Potential ◽  
Sequencing Analysis ◽  
Sequencing Technology ◽  
Single Cell Sequencing

AbstractCirculating tumor cells are tumor cells with high vitality and high metastatic potential that invade and shed into the peripheral blood from primary solid tumors or metastatic foci. Due to the heterogeneity of tumors, it is difficult for high-throughput sequencing analysis of tumor tissues to find the genomic characteristics of low-abundance tumor stem cells. Single-cell sequencing of circulating tumor cells avoids interference from tumor heterogeneity by comparing the differences between single-cell genomes, transcriptomes, and epigenetic groups among circulating tumor cells, primary and metastatic tumors, and metastatic lymph nodes in patients' peripheral blood, providing a new perspective for understanding the biological process of tumors. This article describes the identification, biological characteristics, and single-cell genome-wide variation in circulating tumor cells and summarizes the application of single-cell sequencing technology to tumor typing, metastasis analysis, progression detection, and adjuvant therapy.

#71: Single-cell RNA Sequencing Analysis of Zika Virus Infection in Human Stem Cell-Derived Neuroprogenitor Cells and Cerebral Organoids

2021 ◽  
Vol 10 (Supplement_1) ◽  
pp. S14-S14
Author(s):  
K E Ocwieja ◽  
T K Hughes ◽  
J M Antonucci ◽  
A L Richards ◽  
A C Stanton ◽  
...  
Keyword(s):  
Stem Cell ◽  
Single Cell ◽  
Rna Sequencing ◽  
Zika Virus ◽  
Molecular Mechanisms ◽  
Sequencing Analysis ◽  
Human Stem Cell ◽  
Zikv Infection ◽  
Single Cell Sequencing ◽  
Single Cell Rna Sequencing

Abstract Background The molecular mechanisms underpinning the neurologic and congenital pathologies caused by Zika virus (ZIKV) infection remain poorly understood. It is also unclear why congenital ZIKV disease was not observed prior to the recent epidemics in French Polynesia and the Americas, despite evidence that the Zika virus has actively circulated in parts of Africa and Asia since 1947 and 1966, respectively. Methods Due to advances in stem cell-based technologies, we can now model ZIKV infections of the central nervous system in human stem cell-derived neuroprogenitor cells and cerebral organoids, which recapitulate complex three-dimensional neural architecture. We apply Seq-Well—a simple, portable platform for massively parallel single-cell RNA sequencing—to characterize these neural models infected with ZIKV. We detect and quantify host mRNA transcripts and viral RNA with single-cell resolution, thereby defining transcriptional features of both uninfected and infected cells. Results In neuroprogenitor cells, single-cell sequencing reveals that while uninfected bystander cells strongly upregulate interferon pathway genes, these are largely suppressed in cells infected with ZIKV within the same culture dish. In our organoid model, single-cell sequencing allows us to identify multiple cellular populations, including neuroprogenitor cells, intermediate progenitor cells, and terminally differentiated neurons. In this model of the developing brain, we identify preferred tropisms of ZIKV infection. Our data additionally reveal differences in cell-type frequencies and gene expression within organoids infected by historic and contemporary ZIKV strains from a variety of geographic locations. Conclusions These findings may help explain phenotypic differences attributed to the viruses, including variable propensities to cause microcephaly. Overall, our work provides insight into normal and diseased human brain development and suggests that both virus replication and host response mechanisms underlie the neuropathology of ZIKV infection.

scholarly journals Somatic mutations of activated signaling genes, transcription factors, or tumor suppressors are a precondition for leukemic transformation from myelodysplastic syndromes: a sequencing analysis of 64 paired samples

2021 ◽  
Author(s):  
Xiao Li ◽  
Chun-Kang Chang ◽  
Feng Xu ◽  
Ling-Yun Wu ◽  
Juan Guo ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Single Cell ◽  
Myelodysplastic Syndromes ◽  
Tumor Suppressors ◽  
Somatic Mutations ◽  
Sequencing Analysis ◽  
Single Cell Sequencing ◽  
Paired Samples ◽  
Therapy Targets ◽  
Whole Exome

The transformation biology of secondary AML from MDS is still not fully understood. Here, we performed a large cohort of paired sequences including target, whole-exome and single cell sequencing to search AML transformation- related mutations (TRM). The results showed that fifty-five out of the 64 (85.9%) patients presented presumptive TRM involving activated signaling, transcription factors, or tumor suppressors. Most of TRM (63.6%, 35 cases) emerged at the leukemia transformation point. All five of the remaining nine patients analyzed by paired whole exome sequencing showed TRM which are not included in the reference targets. Single-cell sequencing indicated that the activated cell signaling route was related to TRM which take place prior to phenotypic development. Of note, defined TRM was limited to a small set of genes (less than ten, in the order: NRAS/KRAS, CEBPA, TP53, FLT3, RUNX1, CBL, PTPN11 and WT1, accounted for 91.0% of the mutations). In conclusion, somatic mutations involving in activated signaling, transcription factors, or tumor suppressors appeared to be a precondition for AML transformation from myelodysplastic syndromes. The TRM may be considered as new therapy targets.

scholarly journals Single Cell Sequencing Analysis Identifies Genetics-Modulated ORMDL3+ Cholangiocytes Having Higher Metabolic Effects On Primary Biliary Cholangitis

2021 ◽  
Author(s):  
Bingyu Xiang ◽  
Chunyu Deng ◽  
Fei Qiu ◽  
Jingjing Li ◽  
Shanshan Li ◽  
...  
Keyword(s):  
Single Cell ◽  
Association Studies ◽  
Liver Cells ◽  
Metabolic Effects ◽  
Primary Biliary Cholangitis ◽  
Genome Wide Association Studies ◽  
Sequencing Analysis ◽  
Summary Statistics ◽  
Genetic Determinants ◽  
Single Cell Sequencing

Abstract Background: Primary biliary cholangitis (PBC) is a classical autoimmune disease, which is highly influenced by genetic determinants. Many genome-wide association studies (GWAS) have reported that numerous genetic loci were significantly associated with PBC susceptibility. However, the effects of genetic determinants on liver cells and its immune microenvironment for PBC remain unclear. Results: We constructed a powerful computational framework to integrate GWAS summary statistics with scRNA-seq data to uncover genetics-modulated liver cell subpopulations for PBC. Based on our multi-omics integrative analysis, 29 risk genes including ORMDL3, GSNK2B, and DDAH2 were significantly associated with PBC susceptibility. By combining GWAS summary statistics with scRNA-seq data, we found that cholangiocytes exhibited a notable enrichment by PBC-related genetic association signals (Permuted P < 0.05). The risk gene of ORMDL3 showed the highest expression proportion in cholangiocytes than other liver cells (22.38%). The ORMDL3+ cholangiocytes have prominently higher metabolism activity score than ORMDL3- cholangiocytes (P = 1.383×10-15). Compared with ORMDL3- cholangiocytes, there were 77 significantly differentially expressed genes among ORMDL3+ cholangiocytes (FDR < 0.05), and these significant genes were associated with autoimmune diseases-related functional terms or pathways. The ORMDL3+ cholangiocytes exhibited relatively high communications with macrophage and monocyte. Compared with ORMDL3- cholangiocytes, the VEGF signaling pathway is specific for ORMDL3+ cholangiocytes to interact with other cell populations. Conclusions: To the best of our knowledge, this is the first study to integrate genetic information with single cell sequencing data for parsing genetics-influenced liver cells for PBC risk. We identified that ORMDL3+ cholangiocytes with higher metabolism activity play important immune-modulatory roles in the etiology of PBC.

scholarly journals Single-cell Sequencing in the Field of Stem Cells

2020 ◽  
Vol 21 (8) ◽  
pp. 576-584
Author(s):  
Tian Chen ◽  
Jiawei Li ◽  
Yichen Jia ◽  
Jiyan Wang ◽  
Ruirui Sang ◽  
...  
Keyword(s):  
Stem Cells ◽  
Single Cell ◽  
High Throughput Sequencing ◽  
Acid Extraction ◽  
Sequencing Analysis ◽  
Sequencing Technology ◽  
Single Cell Sequencing ◽  
Continuous Progress ◽  
Basic Characteristics ◽  
Cover Up

Variation and heterogeneity between cells are the basic characteristics of stem cells. Traditional sequencing analysis methods often cover up this difference. Single-cell sequencing technology refers to the technology of high-throughput sequencing analysis of genomes at the single-cell level. It can effectively analyze cell heterogeneity and identify a small number of cell populations. With the continuous progress of cell sorting, nucleic acid extraction and other technologies, single-cell sequencing technology has also made great progress. Encouraging new discoveries have been made in stem cell research, including pluripotent stem cells, tissue-specific stem cells and cancer stem cells. In this review, we discuss the latest progress and future prospects of single-cell sequencing technology in the field of stem cells.

scholarly journals iCellR: Combined Coverage Correction and Principal Component Alignment for Batch Alignment in Single-Cell Sequencing Analysis

2020 ◽  
Author(s):  
Alireza Khodadadi-Jamayran ◽  
Joseph Pucella ◽  
Hua Zhou ◽  
Nicole Doudican ◽  
John Carucci ◽  
...  
Keyword(s):  
Single Cell ◽  
Principal Component ◽  
Drop Out ◽  
Sequencing Analysis ◽  
Component Alignment ◽  
Single Cell Sequencing ◽  
Sequencing Technologies ◽  
Wide Range ◽  
Multiple Samples ◽  
Drop Outs

SUMMARYUnder-sampling RNA molecules and low-coverage sequencing in some single cell sequencing technologies introduce zero counts (also known as drop-outs) into the expression matrices. This issue may complicate the processes of dimensionality reduction and clustering, often forcing distinct cell types to falsely resemble one another, while eliminating subtle, but important differences. Considering the wide range in drop-out rates from different sequencing technologies, it can also affect the analysis at the time of batch/sample alignment and other downstream analyses. Therefore, generating an additional harmonized gene expression matrix is important. To address this, we introduce two separate batch alignment methods: Combined Coverage Correction Alignment (CCCA) and Combined Principal Component Alignment (CPCA). The first method uses a coverage correction approach (analogous to imputation) in a combined or joint fashion between multiple samples for batch alignment, while also correcting for drop-outs in a harmonious way. The second method (CPCA) skips the coverage correction step and uses k nearest neighbors (KNN) for aligning the PCs from the nearest neighboring cells in multiple samples. Our results of nine scRNA-seq PBMC samples from different batches and technologies shows the effectiveness of both these methods. All of our algorithms are implemented in R, deposited into CRAN, and available in the iCellR package.

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