scholarly journals Discovering Cellular Mitochondrial Heteroplasmy Heterogeneity with Single Cell RNA and ATAC Sequencing

Biology ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 503
Author(s):  
Aidan S. Marshall ◽  
Nick S. Jones
Keyword(s):  
Next Generation Sequencing ◽  
Single Cell ◽  
Cellular Heterogeneity ◽  
Open Problems ◽  
Single Cell Sequencing ◽  
Sequencing Technologies ◽  
Single Cell Rna Sequencing ◽  
Mitochondrial Heteroplasmy ◽  
Mitochondrial Heterogeneity ◽  
Generation Sequencing

Next-generation sequencing technologies have revolutionised the study of biological systems by enabling the examination of a broad range of tissues. Its application to single-cell genomics has generated a dynamic and evolving field with a vast amount of research highlighting heterogeneity in transcriptional, genetic and epigenomic state between cells. However, compared to these aspects of cellular heterogeneity, relatively little has been gleaned from single-cell datasets regarding cellular mitochondrial heterogeneity. Single-cell sequencing techniques can provide coverage of the mitochondrial genome which allows researchers to probe heteroplasmies at the level of the single cell, and observe interactions with cellular function. In this review, we give an overview of two popular single-cell modalities—single-cell RNA sequencing and single-cell ATAC sequencing—whose throughput and widespread usage offers researchers the chance to probe heteroplasmy combined with cell state in detailed resolution across thousands of cells. After summarising these technologies in the context of mitochondrial research, we give an overview of recent methods which have used these approaches for discovering mitochondrial heterogeneity. We conclude by highlighting current limitations of these approaches and open problems for future consideration.

scholarly journals Deciphering Tumor Heterogeneity in Hepatocellular Carcinoma (HCC)—Multi-Omic and Singulomic Approaches

2021 ◽  
Author(s):  
Renumathy Dhanasekaran
Keyword(s):  
Single Cell ◽  
Tumor Heterogeneity ◽  
Immune Cell ◽  
Single Cell Analysis ◽  
Sampling Strategies ◽  
Cell Analysis ◽  
Single Cell Sequencing ◽  
Sequencing Technologies ◽  
Hepatocellular Carcinomas ◽  
Generation Sequencing

AbstractTumor heterogeneity, a key hallmark of hepatocellular carcinomas (HCCs), poses a significant challenge to developing effective therapies or predicting clinical outcomes in HCC. Recent advances in next-generation sequencing-based multi-omic and single cell analysis technologies have enabled us to develop high-resolution atlases of tumors and pull back the curtain on tumor heterogeneity. By combining multiregion targeting sampling strategies with deep sequencing of the genome, transcriptome, epigenome, and proteome, several studies have revealed novel mechanistic insights into tumor initiation and progression in HCC. Advances in multiparametric immune cell profiling have facilitated a deeper dive into the biological complexity of HCC, which is crucial in this era of immunotherapy. Moreover, studies using liquid biopsy have demonstrated their potential to circumvent the need for tissue sampling to investigate heterogeneity. In this review, we discuss how multi-omic and single-cell sequencing technologies have advanced our understanding of tumor heterogeneity in HCC.

scholarly journals Cryopreservation of human cancers conserves tumour heterogeneity for single-cell multi-omics analysis

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Sunny Z. Wu ◽  
Daniel L. Roden ◽  
Ghamdan Al-Eryani ◽  
Nenad Bartonicek ◽  
Kate Harvey ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
High Throughput ◽  
Single Cells ◽  
Cellular Heterogeneity ◽  
Tumour Heterogeneity ◽  
Fresh Tissue ◽  
Human Cancers ◽  
Cryopreserved Cell ◽  
Single Cell Rna Sequencing

Abstract Background High throughput single-cell RNA sequencing (scRNA-Seq) has emerged as a powerful tool for exploring cellular heterogeneity among complex human cancers. scRNA-Seq studies using fresh human surgical tissue are logistically difficult, preclude histopathological triage of samples, and limit the ability to perform batch processing. This hindrance can often introduce technical biases when integrating patient datasets and increase experimental costs. Although tissue preservation methods have been previously explored to address such issues, it is yet to be examined on complex human tissues, such as solid cancers and on high throughput scRNA-Seq platforms. Methods Using the Chromium 10X platform, we sequenced a total of ~ 120,000 cells from fresh and cryopreserved replicates across three primary breast cancers, two primary prostate cancers and a cutaneous melanoma. We performed detailed analyses between cells from each condition to assess the effects of cryopreservation on cellular heterogeneity, cell quality, clustering and the identification of gene ontologies. In addition, we performed single-cell immunophenotyping using CITE-Seq on a single breast cancer sample cryopreserved as solid tissue fragments. Results Tumour heterogeneity identified from fresh tissues was largely conserved in cryopreserved replicates. We show that sequencing of single cells prepared from cryopreserved tissue fragments or from cryopreserved cell suspensions is comparable to sequenced cells prepared from fresh tissue, with cryopreserved cell suspensions displaying higher correlations with fresh tissue in gene expression. We showed that cryopreservation had minimal impacts on the results of downstream analyses such as biological pathway enrichment. For some tumours, cryopreservation modestly increased cell stress signatures compared to freshly analysed tissue. Further, we demonstrate the advantage of cryopreserving whole-cells for detecting cell-surface proteins using CITE-Seq, which is impossible using other preservation methods such as single nuclei-sequencing. Conclusions We show that the viable cryopreservation of human cancers provides high-quality single-cells for multi-omics analysis. Our study guides new experimental designs for tissue biobanking for future clinical single-cell RNA sequencing studies.

scholarly journals MBRS-46. CHARTING NEOPLASTIC AND IMMUNE CELL HETEROGENEITY IN HUMAN AND GEM MODELS OF MEDULLOBLASTOMA USING scRNAseq

2020 ◽  
Vol 22 (Supplement_3) ◽  
pp. iii406-iii406
Author(s):  
Andrew Donson ◽  
Kent Riemondy ◽  
Sujatha Venkataraman ◽  
Ahmed Gilani ◽  
Bridget Sanford ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Immune Cell ◽  
Genetically Engineered ◽  
Cellular Heterogeneity ◽  
Cell Heterogeneity ◽  
Transcriptomic Data ◽  
Single Cell Rna Sequencing ◽  
Transcript Profiles

Abstract We explored cellular heterogeneity in medulloblastoma using single-cell RNA sequencing (scRNAseq), immunohistochemistry and deconvolution of bulk transcriptomic data. Over 45,000 cells from 31 patients from all main subgroups of medulloblastoma (2 WNT, 10 SHH, 9 GP3, 11 GP4 and 1 GP3/4) were clustered using Harmony alignment to identify conserved subpopulations. Each subgroup contained subpopulations exhibiting mitotic, undifferentiated and neuronal differentiated transcript profiles, corroborating other recent medulloblastoma scRNAseq studies. The magnitude of our present study builds on the findings of existing studies, providing further characterization of conserved neoplastic subpopulations, including identification of a photoreceptor-differentiated subpopulation that was predominantly, but not exclusively, found in GP3 medulloblastoma. Deconvolution of MAGIC transcriptomic cohort data showed that neoplastic subpopulations are associated with major and minor subgroup subdivisions, for example, photoreceptor subpopulation cells are more abundant in GP3-alpha. In both GP3 and GP4, higher proportions of undifferentiated subpopulations is associated with shorter survival and conversely, differentiated subpopulation is associated with longer survival. This scRNAseq dataset also afforded unique insights into the immune landscape of medulloblastoma, and revealed an M2-polarized myeloid subpopulation that was restricted to SHH medulloblastoma. Additionally, we performed scRNAseq on 16,000 cells from genetically engineered mouse (GEM) models of GP3 and SHH medulloblastoma. These models showed a level of fidelity with corresponding human subgroup-specific neoplastic and immune subpopulations. Collectively, our findings advance our understanding of the neoplastic and immune landscape of the main medulloblastoma subgroups in both humans and GEM models.

Single cell sequencing: An engineer and business person's perspective on how we got here

Lab on a Chip ◽  
2017 ◽  
Vol 17 (20) ◽  
pp. 3349-3350
Author(s):  
Mark Gilligan
Keyword(s):  
Single Cell ◽  
Single Cell Sequencing ◽  
Sequencing Technologies

Microfluidics entrepreneur Mark Gilligan provides a perspective on the development of single-cell sequencing technologies.

scholarly journals Rapid whole-genome mutational profiling using next-generation sequencing technologies

2008 ◽  
Vol 18 (10) ◽  
pp. 1638-1642 ◽  
Author(s):  
D. R. Smith ◽  
A. R. Quinlan ◽  
H. E. Peckham ◽  
K. Makowsky ◽  
W. Tao ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Whole Genome ◽  
Next Generation ◽  
Sequencing Technologies ◽  
Mutational Profiling ◽  
Generation Sequencing

The application of next-generation sequencing technologies to drug discovery and development

2011 ◽  
Vol 16 (11-12) ◽  
pp. 512-519 ◽  
Author(s):  
Peter M. Woollard ◽  
Nalini A.L. Mehta ◽  
Jessica J. Vamathevan ◽  
Stephanie Van Horn ◽  
Bhushan K. Bonde ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Drug Discovery ◽  
Next Generation ◽  
Drug Discovery And Development ◽  
Sequencing Technologies ◽  
Generation Sequencing

scholarly journals Single-cell RNA sequencing of cultured human endometrial CD140b+CD146+ perivascular cells highlights the importance of in vivo microenvironment

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Dandan Cao ◽  
Rachel W. S. Chan ◽  
Ernest H. Y. Ng ◽  
Kristina Gemzell-Danielsson ◽  
William S. B. Yeung
Keyword(s):  
Stem Cells ◽  
Single Cell ◽  
Rna Sequencing ◽  
Marker Gene ◽  
Cellular Heterogeneity ◽  
Stromal Fibroblast ◽  
Perivascular Cells ◽  
Endometrial Cells ◽  
Single Cell Rna Sequencing

Abstract Background Endometrial mesenchymal-like stromal/stem cells (eMSCs) have been proposed as adult stem cells contributing to endometrial regeneration. One set of perivascular markers (CD140b&CD146) has been widely used to enrich eMSCs. Although eMSCs are easily accessible for regenerative medicine and have long been studied, their cellular heterogeneity, relationship to primary counterpart, remains largely unclear. Methods In this study, we applied 10X genomics single-cell RNA sequencing (scRNA-seq) to cultured human CD140b+CD146+ endometrial perivascular cells (ePCs) from menstrual and secretory endometrium. We also analyzed publicly available scRNA-seq data of primary endometrium and performed transcriptome comparison between cultured ePCs and primary ePCs at single-cell level. Results Transcriptomic expression-based clustering revealed limited heterogeneity within cultured menstrual and secretory ePCs. A main subpopulation and a small stress-induced subpopulation were identified in secretory and menstrual ePCs. Cell identity analysis demonstrated the similar cellular composition in secretory and menstrual ePCs. Marker gene expression analysis showed that the main subpopulations identified from cultured secretory and menstrual ePCs simultaneously expressed genes marking mesenchymal stem cell (MSC), perivascular cell, smooth muscle cell, and stromal fibroblast. GO enrichment analysis revealed that genes upregulated in the main subpopulation enriched in actin filament organization, cellular division, etc., while genes upregulated in the small subpopulation enriched in extracellular matrix disassembly, stress response, etc. By comparing subpopulations of cultured ePCs to the publicly available primary endometrial cells, it was found that the main subpopulation identified from cultured ePCs was culture-unique which was unlike primary ePCs or primary endometrial stromal fibroblast cells. Conclusion In summary, these data for the first time provides a single-cell atlas of the cultured human CD140b+CD146+ ePCs. The identification of culture-unique relatively homogenous cell population of CD140b+CD146+ ePCs underscores the importance of in vivo microenvironment in maintaining cellular identity.

Multi tissue processing for single cell sequencing of human immune cells v1

2021 ◽  
Author(s):  
Daniel Rainbow ◽  
Sarah Howlett ◽  
Lorna Jarvis ◽  
Joanne Jones
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Immune Cells ◽  
Human Tissues ◽  
Single Cell Sequencing ◽  
Tissue Processing ◽  
Simultaneous Processing ◽  
Single Cell Rna Sequencing ◽  
Human Immune

This protocol has been developed for the simultaneous processing of multiple human tissues to extract immune cells for single cell RNA sequencing using the 10X platform, and ideal for atlasing projects. Included in this protocol are the steps needed to go from tissue to loading the 10X Chromium for single cell RNA sequencing and includes the hashtag and CiteSeq labelling of cells as well as the details needed to stimulate cells with PMA+I.

scholarly journals Profiling DNA Methylation Based on Next-Generation Sequencing Approaches: New Insights and Clinical Applications

Genes ◽  
2018 ◽  
Vol 9 (9) ◽  
pp. 429 ◽  
Author(s):  
Daniela Barros-Silva ◽  
C. Marques ◽  
Rui Henrique ◽  
Carmen Jerónimo
Keyword(s):  
Dna Methylation ◽  
Next Generation Sequencing ◽  
High Throughput Sequencing ◽  
Epigenetic Modification ◽  
Response To Therapy ◽  
Next Generation ◽  
Sequencing Technologies ◽  
Prognosis And Prediction ◽  
Novel Biomarkers ◽  
Generation Sequencing

DNA methylation is an epigenetic modification that plays a pivotal role in regulating gene expression and, consequently, influences a wide variety of biological processes and diseases. The advances in next-generation sequencing technologies allow for genome-wide profiling of methyl marks both at a single-nucleotide and at a single-cell resolution. These profiling approaches vary in many aspects, such as DNA input, resolution, coverage, and bioinformatics analysis. Thus, the selection of the most feasible method according with the project’s purpose requires in-depth knowledge of those techniques. Currently, high-throughput sequencing techniques are intensively used in epigenomics profiling, which ultimately aims to find novel biomarkers for detection, diagnosis prognosis, and prediction of response to therapy, as well as to discover new targets for personalized treatments. Here, we present, in brief, a portrayal of next-generation sequencing methodologies’ evolution for profiling DNA methylation, highlighting its potential for translational medicine and presenting significant findings in several diseases.

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