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 Accurate SNV detection in single cells by transposon-based whole-genome amplification of complementary strands

2021 ◽  
Vol 118 (8) ◽  
pp. e2013106118
Author(s):  
Dong Xing ◽  
Longzhi Tan ◽  
Chi-Han Chang ◽  
Heng Li ◽  
X. Sunney Xie
Keyword(s):  
Single Cell ◽  
Whole Genome Amplification ◽  
Single Cells ◽  
Human Sperm ◽  
Whole Genome ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Genome Amplification ◽  
Human Blood Cells ◽  
Human Neurons

Single-nucleotide variants (SNVs), pertinent to aging and disease, occur sporadically in the human genome, hence necessitating single-cell measurements. However, detection of single-cell SNVs suffers from false positives (FPs) due to intracellular single-stranded DNA damage and the process of whole-genome amplification (WGA). Here, we report a single-cell WGA method termed multiplexed end-tagging amplification of complementary strands (META-CS), which eliminates nearly all FPs by virtue of DNA complementarity, and achieved the highest accuracy thus far. We validated META-CS by sequencing kindred cells and human sperm, and applied it to other human tissues. Investigation of mature single human neurons revealed increasing SNVs with age and potentially unrepaired strand-specific oxidative guanine damage. We determined SNV frequencies along the genome in differentiated single human blood cells, and identified cell type-dependent mutational patterns for major types of lymphocytes.

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 Single cell transcriptome atlas of mouse mammary epithelial cells across development

2021 ◽  
Vol 23 (1) ◽  
Author(s):  
Bhupinder Pal ◽  
Yunshun Chen ◽  
Michael J. G. Milevskiy ◽  
François Vaillant ◽  
Lexie Prokopuk ◽  
...  
Keyword(s):  
Epithelial Cells ◽  
Single Cell ◽  
Developmental Stages ◽  
Mammary Epithelial Cells ◽  
Expression Profiles ◽  
Single Cells ◽  
Chromatin Accessibility ◽  
Mammary Epithelial ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome

Abstract Background Heterogeneity within the mouse mammary epithelium and potential lineage relationships have been recently explored by single-cell RNA profiling. To further understand how cellular diversity changes during mammary ontogeny, we profiled single cells from nine different developmental stages spanning late embryogenesis, early postnatal, prepuberty, adult, mid-pregnancy, late-pregnancy, and post-involution, as well as the transcriptomes of micro-dissected terminal end buds (TEBs) and subtending ducts during puberty. Methods The single cell transcriptomes of 132,599 mammary epithelial cells from 9 different developmental stages were determined on the 10x Genomics Chromium platform, and integrative analyses were performed to compare specific time points. Results The mammary rudiment at E18.5 closely aligned with the basal lineage, while prepubertal epithelial cells exhibited lineage segregation but to a less differentiated state than their adult counterparts. Comparison of micro-dissected TEBs versus ducts showed that luminal cells within TEBs harbored intermediate expression profiles. Ductal basal cells exhibited increased chromatin accessibility of luminal genes compared to their TEB counterparts suggesting that lineage-specific chromatin is established within the subtending ducts during puberty. An integrative analysis of five stages spanning the pregnancy cycle revealed distinct stage-specific profiles and the presence of cycling basal, mixed-lineage, and 'late' alveolar intermediates in pregnancy. Moreover, a number of intermediates were uncovered along the basal-luminal progenitor cell axis, suggesting a continuum of alveolar-restricted progenitor states. Conclusions This extended single cell transcriptome atlas of mouse mammary epithelial cells provides the most complete coverage for mammary epithelial cells during morphogenesis to date. Together with chromatin accessibility analysis of TEB structures, it represents a valuable framework for understanding developmental decisions within the mouse mammary gland.

scholarly journals MBRS-59. SINGLE-CELL WHOLE-GENOME SEQUENCING DISSECTS INTRA-TUMOURAL GENOMIC HETEROGENEITY AND CLONAL EVOLUTION IN CHILDHOOD MEDULLOBLASTOMA

2020 ◽  
Vol 22 (Supplement_3) ◽  
pp. iii408-iii408
Author(s):  
Marina Danilenko ◽  
Masood Zaka ◽  
Claire Keeling ◽  
Stephen Crosier ◽  
Rafiqul Hussain ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Single Cell ◽  
Genome Sequencing ◽  
Copy Number ◽  
Single Cell Analysis ◽  
Mutational Analysis ◽  
Single Cells ◽  
Clonal Evolution ◽  
Whole Genome ◽  
Clinically Significant

Abstract Medulloblastomas harbor clinically-significant intra-tumoral heterogeneity for key biomarkers (e.g. MYC/MYCN, β-catenin). Recent studies have characterized transcriptional heterogeneity at the single-cell level, however the underlying genomic copy number and mutational architecture remains to be resolved. We therefore sought to establish the intra-tumoural genomic heterogeneity of medulloblastoma at single-cell resolution. Copy number patterns were dissected by whole-genome sequencing in 1024 single cells isolated from multiple distinct tumour regions within 16 snap-frozen medulloblastomas, representing the major molecular subgroups (WNT, SHH, Group3, Group4) and genotypes (i.e. MYC amplification, TP53 mutation). Common copy number driver and subclonal events were identified, providing clear evidence of copy number evolution in medulloblastoma development. Moreover, subclonal whole-arm and focal copy number alterations covering important genomic loci (e.g. on chr10 of SHH patients) were detected in single tumour cells, yet undetectable at the bulk-tumor level. Spatial copy number heterogeneity was also common, with differences between clonal and subclonal events detected in distinct regions of individual tumours. Mutational analysis of the cells allowed dissection of spatial and clonal heterogeneity patterns for key medulloblastoma mutations (e.g. CTNNB1, TP53, SMARCA4, PTCH1) within our cohort. Integrated copy number and mutational analysis is underway to establish their inter-relationships and relative contributions to clonal evolution during tumourigenesis. In summary, single-cell analysis has enabled the resolution of common mutational and copy number drivers, alongside sub-clonal events and distinct patterns of clonal and spatial evolution, in medulloblastoma development. We anticipate these findings will provide a critical foundation for future improved biomarker selection, and the development of targeted therapies.

scholarly journals Three-dimensional genome structures of single diploid human cells

Science ◽  
2018 ◽  
Vol 361 (6405) ◽  
pp. 924-928 ◽  
Author(s):  
Longzhi Tan ◽  
Dong Xing ◽  
Chi-Han Chang ◽  
Heng Li ◽  
X. Sunney Xie
Keyword(s):  
Single Cell ◽  
Three Dimensional ◽  
Copy Number Variations ◽  
Human Cells ◽  
X Chromosomes ◽  
Structural Cell ◽  
Cell Functions ◽  
Amplification Method ◽  
Capture Method ◽  
Diploid Cells

Three-dimensional genome structures play a key role in gene regulation and cell functions. Characterization of genome structures necessitates single-cell measurements. This has been achieved for haploid cells but has remained a challenge for diploid cells. We developed a single-cell chromatin conformation capture method, termed Dip-C, that combines a transposon-based whole-genome amplification method to detect many chromatin contacts, called META (multiplex end-tagging amplification), and an algorithm to impute the two chromosome haplotypes linked by each contact. We reconstructed the genome structures of single diploid human cells from a lymphoblastoid cell line and from primary blood cells with high spatial resolution, locating specific single-nucleotide and copy number variations in the nucleus. The two alleles of imprinted loci and the two X chromosomes were structurally different. Cells of different types displayed statistically distinct genome structures. Such structural cell typing is crucial for understanding cell functions.

scholarly journals Single cell transcriptome in aneuploidies reveals mechanisms of gene dosage imbalance

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Georgios Stamoulis ◽  
Marco Garieri ◽  
Periklis Makrythanasis ◽  
Audrey Letourneau ◽  
Michel Guipponi ◽  
...  
Keyword(s):  
Single Cell ◽  
Gene Dosage ◽  
Single Cells ◽  
Phenotypic Variability ◽  
Specific Expression ◽  
Altered Gene ◽  
Discordant Twins ◽  
Cell Transcriptome ◽  
Improved Model ◽  
Dosage Imbalance

Abstract Aneuploidy is a major source of gene dosage imbalance due to copy number alterations (CNA), and viable human trisomies are model disorders of altered gene expression. We study gene and allele-specific expression (ASE) of 9668 single-cell fibroblasts from trisomy 21 (T21) discordant twins and from mosaic T21, T18, T13 and T8. We examine 928 single cells with deep scRNAseq. Expected and observed overexpression of trisomic genes in trisomic vs. diploid bulk RNAseq is not detectable in trisomic vs. diploid single cells. Instead, for trisomic genes with low-to-average expression, their altered gene dosage is mainly due to the higher fraction of trisomic cells simultaneously expressing these genes, in agreement with a stochastic 2-state burst-like model of transcription. These results, confirmed in a further analysis of 8740 single fibroblasts with shallow scRNAseq, suggest that the specific transcriptional profile of each gene contributes to the phenotypic variability of trisomies. We propose an improved model to understand the effects of CNA and, generally, of gene regulation on gene dosage imbalance.

scholarly journals Combined Molecular Genetic and Cytogenetic Analysis from Single Cells after Isothermal Whole-Genome Amplification

2011 ◽  
Vol 57 (7) ◽  
pp. 1032-1041 ◽  
Author(s):  
Thomas Kroneis ◽  
Jochen B Geigl ◽  
Amin El-Heliebi ◽  
Martina Auer ◽  
Peter Ulz ◽  
...  
Keyword(s):  
Single Cell ◽  
Tumor Cells ◽  
Whole Genome Amplification ◽  
Single Cells ◽  
Molecular Genetic ◽  
Target Cells ◽  
Whole Genome ◽  
Single Cell Level ◽  
Cell Level ◽  
Genome Amplification

BACKGROUND Analysis of chromosomal aberrations or single-gene disorders from rare fetal cells circulating in the blood of pregnant women requires verification of the cells' genomic identity. We have developed a method enabling multiple analyses at the single-cell level that combines verification of the genomic identity of microchimeric cells with molecular genetic and cytogenetic diagnosis. METHODS We used a model system of peripheral blood mononuclear cells spiked with a colon adenocarcinoma cell line and immunofluorescence staining for cytokeratin in combination with DNA staining with the nuclear dye TO-PRO-3 in a preliminary study to define candidate microchimeric (tumor) cells in Cytospin preparations. After laser microdissection, we performed low-volume on-chip isothermal whole-genome amplification (iWGA) of single and pooled cells. RESULTS DNA fingerprint analysis of iWGA aliquots permitted successful identification of all analyzed candidate microchimeric cell preparations (6 samples of pooled cells, 7 samples of single cells). Sequencing of 3 single-nucleotide polymorphisms was successful at the single-cell level for 20 of 32 allelic loci. Metaphase comparative genomic hybridization (mCGH) with iWGA products of single cells showed the gains and losses known to be present in the genomic DNA of the target cells. CONCLUSIONS This method may be instrumental in cell-based noninvasive prenatal diagnosis. Furthermore, the possibility to perform mCGH with amplified DNA from single cells offers a perspective for the analysis of nonmicrochimeric rare cells exhibiting genomic alterations, such as circulating tumor cells.

scholarly journals Accurate identification of single-nucleotide variants in whole-genome-amplified single cells

2017 ◽  
Vol 14 (5) ◽  
pp. 491-493 ◽  
Author(s):  
Xiao Dong ◽  
Lei Zhang ◽  
Brandon Milholland ◽  
Moonsook Lee ◽  
Alexander Y Maslov ◽  
...  
Keyword(s):  
Single Cells ◽  
Whole Genome ◽  
Single Nucleotide Variants ◽  
Accurate Identification ◽  
Single Nucleotide

scholarly journals BAMM-SC: A Bayesian mixture model for clustering droplet-based single cell transcriptomic data from population studies

2018 ◽  
Author(s):  
Zhe Sun ◽  
Li Chen ◽  
Hongyi Xin ◽  
Qianhui Huang ◽  
Anthony R Cillo ◽  
...  
Keyword(s):  
Single Cell ◽  
Single Cells ◽  
R Package ◽  
Clustering Methods ◽  
Model Framework ◽  
Bayesian Hierarchical ◽  
Bayesian Mixture ◽  
Population Scale ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome

AbstractThe recently developed droplet-based single cell transcriptome sequencing (scRNA-seq) technology makes it feasible to perform a population-scale scRNA-seq study, in which the transcriptome is measured for tens of thousands of single cells from multiple individuals. Despite the advances of many clustering methods, there are few tailored methods for population-scale scRNA-seq studies. Here, we have developed a BAyesiany Mixture Model for Single Cell sequencing (BAMM-SC) method to cluster scRNA-seq data from multiple individuals simultaneously. Specifically, BAMM-SC takes raw data as input and can account for data heterogeneity and batch effect among multiple individuals in a unified Bayesian hierarchical model framework. Results from extensive simulations and application of BAMM-SC to in-house scRNA-seq datasets using blood, lung and skin cells from humans or mice demonstrated that BAMM-SC outperformed existing clustering methods with improved clustering accuracy and reduced impact from batch effects. BAMM-SC has been implemented in a user-friendly R package with a detailed tutorial available on www.pitt.edu/~Cwec47/singlecell.html.

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