scholarly journals Topologically Dependent Abundance of Spontaneous DNA Damage in Single Human Cells

2019 ◽  
Author(s):  
Qiangyuan Zhu ◽  
Yichi Niu ◽  
Michael Gundry ◽  
Kuanwei Sheng ◽  
Muchun Niu ◽  
...  
Keyword(s):  
Dna Damage ◽  
Single Cell ◽  
Genome Stability ◽  
De Novo ◽  
Single Cells ◽  
Human Cells ◽  
Single Nucleotide Variants ◽  
Genome Wide ◽  
First Time

AbstractIn the studies of single-cell genomics, the large endeavor has been focused on the detection of the permanent changes in the genome. On the other hand, spontaneous DNA damage frequently occurs and results in transient single-stranded changes to the genome until they are repaired. So far, successful profiling of these dynamic changes has not been demonstrated by single-cell whole-genome amplification methods. Here we reported a novel single-cell WGA method: Linearly Produced Semiamplicon based Split Amplification Reaction (LPSSAR), which allows, for the first time, the genome-wide detection of the DNA damage associated single nucleotide variants (dSNVs) in single human cells. The sequence-based detection of dSNVs allows the direct characterization of the major damage signature that occurred in human cells. In the analysis of the abundance of dSNVs along the genome, we observed two modules of dSNV abundance, instead of a homogeneous abundance of dSNVs. Interestingly, we found that the two modules are associated with the A/B topological compartments of the genome. This result suggests that the genome topology directly influences genome stability. Furthermore, with the detection of a large number of dSNVs in single cells, we showed that only under a stringent filtering condition, can we distinguish the de novo mutations from the dSNVs and achieve a reliable estimation of the total level of de novo mutations in a single cell.

scholarly journals ChromVAR: Inferring transcription factor variation from single-cell epigenomic data

2017 ◽  
Author(s):  
Alicia N. Schep ◽  
Beijing Wu ◽  
Jason D. Buenrostro ◽  
William J. Greenleaf
Keyword(s):  
Transcription Factor ◽  
Single Cell ◽  
De Novo ◽  
Single Cells ◽  
R Package ◽  
Chromatin Accessibility ◽  
Data Sets ◽  
Sequence Motifs ◽  
Computational Approaches

AbstractSingle cell ATAC-seq (scATAC) yields sparse data that makes application of conventional computational approaches for data analysis challenging or impossible. We developed chromVAR, an R package for analyzing sparse chromatin accessibility data by estimating the gain or loss of accessibility within sets of peaks sharing the same motif or annotation while controlling for known technical biases. chromVAR enables accurate clustering of scATAC-seq profiles and enables characterization of known, or the de novo identification of novel, sequence motifs associated with variation in chromatin accessibility across single cells or other sparse epigenomic data sets.

scholarly journals Single-cell damagenome profiling unveils vulnerable genes and functional pathways in human genome toward DNA damage

2021 ◽  
Vol 7 (27) ◽  
pp. eabf3329
Author(s):  
Qiangyuan Zhu ◽  
Yichi Niu ◽  
Michael Gundry ◽  
Chenghang Zong
Keyword(s):  
Dna Damage ◽  
Single Cell ◽  
Single Cells ◽  
Three Dimensional ◽  
Autism Spectrum ◽  
Whole Genome ◽  
Single Nucleotide Variants ◽  
Amplification Method ◽  
Human Neurons ◽  
Cell Transcriptome

We report a novel single-cell whole-genome amplification method (LCS-WGA) that can efficiently capture spontaneous DNA damage existing in single cells. We refer to these damage-associated single-nucleotide variants as “damSNVs,” and the whole-genome distribution of damSNVs as the damagenome. We observed that in single human neurons, the damagenome distribution was significantly correlated with three-dimensional genome structures. This nonuniform distribution indicates different degrees of DNA damage effects on different genes. Next, we identified the functionals that were significantly enriched in the high-damage genes. Similar functionals were also enriched in the differentially expressed genes (DEGs) detected by single-cell transcriptome of both Alzheimer’s disease (AD) and autism spectrum disorder (ASD). This result can be explained by the significant enrichment of high-damage genes in the DEGs of neurons for both AD and ASD. The discovery of high-damage genes sheds new lights on the important roles of DNA damage in human diseases and disorders.

scholarly journals RA3 is a reference-guided approach for epigenetic characterization of single cells

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Shengquan Chen ◽  
Guanao Yan ◽  
Wenyu Zhang ◽  
Jinzhao Li ◽  
Rui Jiang ◽  
...  
Keyword(s):  
Single Cell ◽  
Computational Analysis ◽  
Reference Data ◽  
Single Cells ◽  
Chromatin Accessibility ◽  
Biological Variation ◽  
Superior Performance ◽  
High Dimensionality ◽  
High Degree

AbstractThe recent advancements in single-cell technologies, including single-cell chromatin accessibility sequencing (scCAS), have enabled profiling the epigenetic landscapes for thousands of individual cells. However, the characteristics of scCAS data, including high dimensionality, high degree of sparsity and high technical variation, make the computational analysis challenging. Reference-guided approaches, which utilize the information in existing datasets, may facilitate the analysis of scCAS data. Here, we present RA3 (Reference-guided Approach for the Analysis of single-cell chromatin Accessibility data), which utilizes the information in massive existing bulk chromatin accessibility and annotated scCAS data. RA3 simultaneously models (1) the shared biological variation among scCAS data and the reference data, and (2) the unique biological variation in scCAS data that identifies distinct subpopulations. We show that RA3 achieves superior performance when used on several scCAS datasets, and on references constructed using various approaches. Altogether, these analyses demonstrate the wide applicability of RA3 in analyzing scCAS data.

scholarly journals Reconstructing single-cell karyotype alterations in colorectal cancer identifies punctuated and gradual diversification patterns

2021 ◽  
Author(s):  
Yannik Bollen ◽  
Ellen Stelloo ◽  
Petra van Leenen ◽  
Myrna van den Bos ◽  
Bas Ponsioen ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Single Cell ◽  
Temporal Dynamics ◽  
De Novo ◽  
Tumor Evolution ◽  
Genome Wide ◽  
Aneuploid Tumor ◽  
Evolutionary Paths ◽  
Tumor Biopsies ◽  
Punctuated Evolution

AbstractCentral to tumor evolution is the generation of genetic diversity. However, the extent and patterns by which de novo karyotype alterations emerge and propagate within human tumors are not well understood, especially at single-cell resolution. Here, we present 3D Live-Seq—a protocol that integrates live-cell imaging of tumor organoid outgrowth and whole-genome sequencing of each imaged cell to reconstruct evolving tumor cell karyotypes across consecutive cell generations. Using patient-derived colorectal cancer organoids and fresh tumor biopsies, we demonstrate that karyotype alterations of varying complexity are prevalent and can arise within a few cell generations. Sub-chromosomal acentric fragments were prone to replication and collective missegregation across consecutive cell divisions. In contrast, gross genome-wide karyotype alterations were generated in a single erroneous cell division, providing support that aneuploid tumor genomes can evolve via punctuated evolution. Mapping the temporal dynamics and patterns of karyotype diversification in cancer enables reconstructions of evolutionary paths to malignant fitness.

scholarly journals Characterization of CRISPR/Cas9 RANKL knockout mesenchymal stem cell clones based on single-cell printing technology and emulsion coupling assay as a low-cellularity workflow for single-cell cloning

2020 ◽  
Author(s):  
Tobias Groß ◽  
Csaba Jeney ◽  
Darius Halm ◽  
Günter Finkenzeller ◽  
G. Björn Stark ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Line ◽  
Large Scale ◽  
Single Cells ◽  
Protein Detection ◽  
Cell Line Development ◽  
Cell Printing ◽  
Cell Clones ◽  
The University

AbstractThe homogeneity of the genetically modified single-cells is a necessity for many applications such as cell line development, gene therapy, and tissue engineering and in particular for regenerative medical applications. The lack of tools to effectively isolate and characterize CRISPR/Cas9 engineered cells is considered as a significant bottleneck in these applications. Especially the incompatibility of protein detection technologies to confirm protein expression changes without a preconditional large-scale clonal expansion, creates a gridlock in many applications. To ameliorate the characterization of engineered cells, we propose an improved workflow, including single-cell printing/isolation technology based on fluorescent properties with high yield, a genomic edit screen (surveyor assay), mRNA rtPCR assessing altered gene expression and a versatile protein detection tool called emulsion-coupling to deliver a high-content, unified single-cell workflow. The workflow was exemplified by engineering and functionally validating RANKL knockout immortalized mesenchymal stem cells showing altered bone formation capacity of these cells. The resulting workflow is economical, without the requirement of large-scale clonal expansions of the cells with overall cloning efficiency above 30% of CRISPR/Cas9 edited cells. Nevertheless, as the single-cell clones are comprehensively characterized at an early, highly parallel phase of the development of cells including DNA, RNA, and protein levels, the workflow delivers a higher number of successfully edited cells for further characterization, lowering the chance of late failures in the development process.Author summaryI completed my undergraduate degree in biochemistry at the University of Ulm and finished my master's degree in pharmaceutical biotechnology at the University of Ulm and University of applied science of Biberach with a focus on biotechnology, toxicology and molecular biology. For my master thesis, I went to the University of Freiburg to the department of microsystems engineering, where I developed a novel workflow for cell line development. I stayed at the institute for my doctorate, but changed my scientific focus to the development of the emulsion coupling technology, which is a powerful tool for the quantitative and highly parallel measurement of protein and protein interactions. I am generally interested in being involved in the development of innovative molecular biological methods that can be used to gain new insights about biological issues. I am particularly curious to unravel the complex and often poorly understood protein interaction pathways that are the cornerstone of understanding cellular functionality and are a fundamental necessity to describe life mechanistically.

scholarly journals Fully phased human genome assembly without parental data using single-cell strand sequencing and long reads

2020 ◽  
Author(s):  
David Porubsky ◽  
◽  
Peter Ebert ◽  
Peter A. Audano ◽  
Mitchell R. Vollger ◽  
...  
Keyword(s):  
Single Cell ◽  
Genome Assembly ◽  
De Novo ◽  
Error Rates ◽  
Sequencing Data ◽  
Single Nucleotide Variants ◽  
De Novo Genome Assembly ◽  
Parental Data ◽  
Human Genome Assembly ◽  
Long Read

AbstractHuman genomes are typically assembled as consensus sequences that lack information on parental haplotypes. Here we describe a reference-free workflow for diploid de novo genome assembly that combines the chromosome-wide phasing and scaffolding capabilities of single-cell strand sequencing1,2 with continuous long-read or high-fidelity3 sequencing data. Employing this strategy, we produced a completely phased de novo genome assembly for each haplotype of an individual of Puerto Rican descent (HG00733) in the absence of parental data. The assemblies are accurate (quality value > 40) and highly contiguous (contig N50 > 23 Mbp) with low switch error rates (0.17%), providing fully phased single-nucleotide variants, indels and structural variants. A comparison of Oxford Nanopore Technologies and Pacific Biosciences phased assemblies identified 154 regions that are preferential sites of contig breaks, irrespective of sequencing technology or phasing algorithms.

scholarly journals DNA Analysis by Restriction Enzyme (DARE) enables concurrent genomic and epigenomic characterization of single cells

2019 ◽  
Vol 47 (19) ◽  
pp. e122-e122
Author(s):  
Ramya Viswanathan ◽  
Elsie Cheruba ◽  
Lih Feng Cheow
Keyword(s):  
Dna Methylation ◽  
Restriction Enzyme ◽  
Copy Number ◽  
Dna Analysis ◽  
Whole Genome Amplification ◽  
Single Cells ◽  
Whole Genome ◽  
Copy Number Alterations ◽  
Genome Wide

Abstract Genome-wide profiling of copy number alterations and DNA methylation in single cells could enable detailed investigation into the genomic and epigenomic heterogeneity of complex cell populations. However, current methods to do this require complex sample processing and cleanup steps, lack consistency, or are biased in their genomic representation. Here, we describe a novel single-tube enzymatic method, DNA Analysis by Restriction Enzyme (DARE), to perform deterministic whole genome amplification while preserving DNA methylation information. This method was evaluated on low amounts of DNA and single cells, and provides accurate copy number aberration calling and representative DNA methylation measurement across the whole genome. Single-cell DARE is an attractive and scalable approach for concurrent genomic and epigenomic characterization of cells in a heterogeneous population.

scholarly journals The RAD51 recombinase protects mitotic chromatin in human cells

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Isabel E. Wassing ◽  
Emily Graham ◽  
Xanita Saayman ◽  
Lucia Rampazzo ◽  
Christine Ralf ◽  
...  
Keyword(s):  
Chromosome Segregation ◽  
Genome Stability ◽  
Spindle Assembly Checkpoint ◽  
De Novo ◽  
Genomic Stability ◽  
Human Cells ◽  
Genome Integrity ◽  
Chromosomal Replication ◽  
Anaphase Onset ◽  
Mitotic Chromatin

AbstractThe RAD51 recombinase plays critical roles in safeguarding genome integrity, which is fundamentally important for all living cells. While interphase functions of RAD51 in maintaining genome stability are well-characterised, its role in mitosis remains contentious. In this study, we show that RAD51 protects under-replicated DNA in mitotic human cells and, in this way, promotes mitotic DNA synthesis (MiDAS) and successful chromosome segregation. In cells experiencing mild replication stress, MiDAS was detected irrespective of mitotically generated DNA damage. MiDAS broadly required de novo RAD51 recruitment to single-stranded DNA, which was supported by the phosphorylation of RAD51 by the key mitotic regulator Polo-like kinase 1. Importantly, acute inhibition of MiDAS delayed anaphase onset and induced centromere fragility, suggesting a mechanism that prevents the satisfaction of the spindle assembly checkpoint while chromosomal replication remains incomplete. This study hence identifies an unexpected function of RAD51 in promoting genomic stability in mitosis.

scholarly journals Scirpy: A Scanpy extension for analyzing single-cell T-cell receptor sequencing data

2020 ◽  
Author(s):  
Gregor Sturm ◽  
Tamas Szabo ◽  
Georgios Fotakis ◽  
Marlene Haider ◽  
Dietmar Rieder ◽  
...  
Keyword(s):  
T Cell ◽  
Single Cell ◽  
Large Scale ◽  
Single Cells ◽  
Cell Receptor ◽  
Sequencing Data ◽  
Seamless Integration ◽  
T Cell Phenotypes ◽  
Cell Phenotypes

AbstractSummaryAdvances in single-cell technologies have enabled the investigation of T cell phenotypes and repertoires at unprecedented resolution and scale. Bioinformatic methods for the efficient analysis of these large-scale datasets are instrumental for advancing our understanding of adaptive immune responses in cancer, but also in infectious diseases like COVID-19. However, while well-established solutions are accessible for the processing of single-cell transcriptomes, no streamlined pipelines are available for the comprehensive characterization of T cell receptors. Here we propose Scirpy, a scalable Python toolkit that provides simplified access to the analysis and visualization of immune repertoires from single cells and seamless integration with transcriptomic data.Availability and implementationScirpy source code and documentation are available at https://github.com/icbi-lab/scirpy.

scholarly journals Elucidation of tumor-stromal heterogeneity and the ligand-receptor interactome by single cell transcriptomics in real-world pancreatic cancer biopsies

2020 ◽  
Author(s):  
Jaewon Lee ◽  
Vincent Bernard ◽  
Alexander Semaan ◽  
Maria Monberg ◽  
Jonathan Huang ◽  
...  
Keyword(s):  
Single Cell ◽  
Clinical Decision Making ◽  
De Novo ◽  
Ex Vivo ◽  
Clinical Decision ◽  
Ductal Adenocarcinoma ◽  
Cancer Associated Fibroblast ◽  
Parental Tumor

Abstract Precision medicine approaches in pancreatic ductal adenocarcinoma (PDAC) are imperative for improving disease outcomes. However, the long-term fidelity of recently deployed ex vivo preclinical platforms, such as patient-derived organoids (PDOs), remains unknown. Through single-cell RNA sequencing (scRNA-seq), we identify substantial transcriptomic evolution of PDOs propagated from the parental tumor, which may alter predicted drug sensitivity. In contrast, scRNA-seq is readily applicable to limited biopsies from human primary and metastatic PDAC and identifies most cancers as being an admixture of previously described epithelial transcriptomic subtypes. Integrative analyses of our data provide an in-depth characterization of the heterogeneity within the tumor microenvironment, including cancer-associated fibroblast (CAF) subclasses, and predict a multitude of ligand-receptor interactions, revealing potential targets for immunotherapy approaches. While PDOs continue to enable prospective therapeutic prediction, our analysis also demonstrates the complementarity of using orthogonal de novo biopsies from PDAC patients paired with scRNA-seq to inform clinical decision-making.

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