scholarly journals A Shift in Paradigms: Spatial Genomics Approaches to Reveal Single-Cell Principles of Genome Organization

2021 ◽  
Vol 12 ◽  
Author(s):  
Andres M. Cardozo Gizzi
Keyword(s):  
Single Cell ◽  
Genome Organization ◽  
Spatial Information ◽  
Genome Structure ◽  
Main Question ◽  
Nuclear Speckles ◽  
Technological Advances ◽  
Functional Consequences ◽  
Cell Processes ◽  
Nuclear Structures

The genome tridimensional (3D) organization and its role towards the regulation of key cell processes such as transcription is currently a main question in biology. Interphase chromosomes are spatially segregated into “territories,” epigenetically-defined large domains of chromatin that interact to form “compartments” with common transcriptional status, and insulator-flanked domains called “topologically associating domains” (TADs). Moreover, chromatin organizes around nuclear structures such as lamina, speckles, or the nucleolus to acquire a higher-order genome organization. Due to recent technological advances, the different hierarchies are being solved. Particularly, advances in microscopy technologies are shedding light on the genome structure at multiple levels. Intriguingly, more and more reports point to high variability and stochasticity at the single-cell level. However, the functional consequences of such variability in genome conformation are still unsolved. Here, I will discuss the implication of the cell-to-cell heterogeneity at the different scales in the context of newly developed imaging approaches, particularly multiplexed Fluorescence in situ hybridization methods that enabled “chromatin tracing.” Extensions of these methods are now combining spatial information of dozens to thousands of genomic loci with the localization of nuclear features such as the nucleolus, nuclear speckles, or even histone modifications, creating the fast-moving field of “spatial genomics.” As our view of genome organization shifts the focus from ensemble to single-cell, new insights to fundamental questions begin to emerge.

scholarly journals A single-cell method to map higher-order 3D genome organization in thousands of individual cells reveals structural heterogeneity in mouse ES cells

2020 ◽  
Author(s):  
Mary V. Arrastia ◽  
Joanna W. Jachowicz ◽  
Noah Ollikainen ◽  
Matthew S. Curtis ◽  
Charlotte Lai ◽  
...  
Keyword(s):  
Single Cell ◽  
Genome Organization ◽  
Single Cells ◽  
Genome Structure ◽  
Higher Order ◽  
Nuclear Bodies ◽  
Nuclear Function ◽  
Genome Wide ◽  
A Genome ◽  
Order Structures

ABSTRACTIn eukaryotes, the nucleus is organized into a three dimensional structure consisting of both local interactions such as those between enhancers and promoters, and long-range higher-order structures such as nuclear bodies. This organization is central to many aspects of nuclear function, including DNA replication, transcription, and cell cycle progression. Nuclear structure intrinsically occurs within single cells; however, measuring such a broad spectrum of 3D DNA interactions on a genome-wide scale and at the single cell level has been a great challenge. To address this, we developed single-cell split-pool recognition of interactions by tag extension (scSPRITE), a new method that enables measurements of genome-wide maps of 3D DNA structure in thousands of individual nuclei. scSPRITE maximizes the number of DNA contacts detected per cell enabling high-resolution genome structure maps within each cells and is easy-to-use and cost-effective. scSPRITE accurately detects chromosome territories, active and inactive compartments, topologically associating domains (TADs), and higher-order structures within single cells. In addition, scSPRITE measures cell-to-cell heterogeneity in genome structure at different levels of resolution and shows that TADs are dynamic units of genome organization that can vary between different cells within a population. scSPRITE will improve our understanding of nuclear architecture and its relationship to nuclear function within an individual nucleus from complex cell types and tissues containing a diverse population of cells.

Technological advances in single-cell genomic analyses

2011 ◽  
Vol 33 (1) ◽  
pp. 17-24 ◽  
Author(s):  
Xing-Hua PAN ◽  
Hai-Ying ZHU ◽  
Sadie L MARJANI
Keyword(s):  
Single Cell ◽  
Technological Advances ◽  
Genomic Analyses

4 Molecularly guided multiplexed digital spatial analysis reveals differential gene expression profiles in the WNT-β-catenin pathway between melanoma and prostate tumors

2020 ◽  
Vol 8 (Suppl 3) ◽  
pp. A4-A4
Author(s):  
Anushka Dikshit ◽  
Dan Zollinger ◽  
Karen Nguyen ◽  
Jill McKay-Fleisch ◽  
Kit Fuhrman ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Single Molecule ◽  
Spatial Information ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Fluorescence Assay ◽  
Differentially Expressed ◽  
Tumor Type ◽  
Prostate Tumors

BackgroundThe canonical WNT-β-catenin signaling pathway is vital for development and tissue homeostasis but becomes strongly tumorigenic when dysregulated. and alter the transcriptional signature of a cell to promote malignant transformation. However, thorough characterization of these transcriptomic signatures has been challenging because traditional methods lack either spatial information, multiplexing, or sensitivity/specificity. To overcome these challenges, we developed a novel workflow combining the single molecule and single cell visualization capabilities of the RNAscope in situ hybridization (ISH) assay with the highly multiplexed spatial profiling capabilities of the GeoMx™ Digital Spatial Profiler (DSP) RNA assays. Using these methods, we sought to spatially profile and compare gene expression signatures of tumor niches with high and low CTNNB1 expression.MethodsAfter screening 120 tumor cores from multiple tumors for CTNNB1 expression by the RNAscope assay, we identified melanoma as the tumor type with the highest CTNNB1 expression while prostate tumors had the lowest expression. Using the RNAscope Multiplex Fluorescence assay we selected regions of high CTNNB1 expression within 3 melanoma tumors as well as regions with low CTNNB1 expression within 3 prostate tumors. These selected regions of interest (ROIs) were then transcriptionally profiled using the GeoMx DSP RNA assay for a set of 78 genes relevant in immuno-oncology. Target genes that were differentially expressed were further visualized and spatially assessed using the RNAscope Multiplex Fluorescence assay to confirm GeoMx DSP data with single cell resolution.ResultsThe GeoMx DSP analysis comparing the melanoma and prostate tumors revealed that they had significantly different gene expression profiles and many of these genes showed concordance with CTNNB1 expression. Furthermore, immunoregulatory targets such as ICOSLG, CTLA4, PDCD1 and ARG1, also demonstrated significant correlation with CTNNB1 expression. On validating selected targets using the RNAscope assay, we could distinctly visualize that they were not only highly expressed in melanoma compared to the prostate tumor, but their expression levels changed proportionally to that of CTNNB1 within the same tumors suggesting that these differentially expressed genes may be regulated by the WNT-β-catenin pathway.ConclusionsIn summary, by combining the RNAscope ISH assay and the GeoMx DSP RNA assay into one joint workflow we transcriptionally profiled regions of high and low CTNNB1 expression within melanoma and prostate tumors and identified genes potentially regulated by the WNT- β-catenin pathway. This novel workflow can be fully automated and is well suited for interrogating the tumor and stroma and their interactions.GeoMx Assays are for RESEARCH ONLY, not for diagnostics.

The 3D Genome Structure of Single Cells

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Tianming Zhou ◽  
Ruochi Zhang ◽  
Jian Ma
Keyword(s):  
Single Cell ◽  
Data Science ◽  
Spatial Organization ◽  
Method Development ◽  
Single Cells ◽  
Genome Structure ◽  
Computational Method ◽  
Publication Date ◽  
3D Genome ◽  
Genome Features

The spatial organization of the genome in the cell nucleus is pivotal to cell function. However, how the 3D genome organization and its dynamics influence cellular phenotypes remains poorly understood. The very recent development of single-cell technologies for probing the 3D genome, especially single-cell Hi-C (scHi-C), has ushered in a new era of unveiling cell-to-cell variability of 3D genome features at an unprecedented resolution. Here, we review recent developments in computational approaches to the analysis of scHi-C, including data processing, dimensionality reduction, imputation for enhancing data quality, and the revealing of 3D genome features at single-cell resolution. While much progress has been made in computational method development to analyze single-cell 3D genomes, substantial future work is needed to improve data interpretation and multimodal data integration, which are critical to reveal fundamental connections between genome structure and function among heterogeneous cell populations in various biological contexts. Expected final online publication date for the Annual Review of Biomedical Data Science, Volume 4 is July 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

scholarly journals Cell-to-cell heterogeneity in Escherichia coli stress response originates from pulsatile expression and growth

2020 ◽  
Author(s):  
Nadia M. V. Sampaio ◽  
Caroline M. Blassick ◽  
Jean-Baptiste Lugagne ◽  
Mary J. Dunlop
Keyword(s):  
Gene Expression ◽  
Escherichia Coli ◽  
Stress Response ◽  
Single Cell ◽  
Phenotypic Variability ◽  
Growth Dynamics ◽  
Time Lapse ◽  
Cell Heterogeneity ◽  
Temporal Expression ◽  
Functional Consequences

AbstractCell-to-cell heterogeneity in gene expression and growth can have critical functional consequences, such as determining whether individual bacteria survive or die following stress. Although phenotypic variability is well documented, the dynamics that underlie it are often unknown. This information is critical because dramatically different outcomes can arise from gradual versus rapid changes in expression and growth. Using single-cell time-lapse microscopy, we measured the temporal expression of a suite of stress response reporters in Escherichia coli, while simultaneously monitoring growth rate. In conditions without stress, we found widespread examples of pulsatile expression. Single-cell growth rates were often anti-correlated with gene expression, with changes in growth preceding changes in expression. These pulsatile dynamics have functional consequences, which we demonstrate by measuring survival after challenging cells with the antibiotic ciprofloxacin. Our results suggest that pulsatile expression and growth dynamics are common in stress response networks and can have direct consequences for survival.

scholarly journals Haplotype-aware single-cell multiomics uncovers functional effects of somatic structural variation

2021 ◽  
Author(s):  
Hyobin Jeong ◽  
Karen Grimes ◽  
Peter-Martin Bruch ◽  
Tobias Rausch ◽  
Patrick Hasenfeld ◽  
...  
Keyword(s):  
Single Cell ◽  
Nucleosome Occupancy ◽  
Single Cells ◽  
Chromosomal Rearrangements ◽  
Regulatory Elements ◽  
Computational Method ◽  
Tumour Heterogeneity ◽  
Cancer Genomes ◽  
Functional Consequences ◽  
Oncogenic Transcription Factor

Somatic structural variants (SVs) are widespread in cancer genomes, however, their impact on tumorigenesis and intra-tumour heterogeneity is incompletely understood, since methods to functionally characterize the broad spectrum of SVs arising in cancerous single-cells are lacking. We present a computational method, scNOVA, that couples SV discovery with nucleosome occupancy analysis by haplotype-resolved single-cell sequencing, to systematically uncover SV effects on cis-regulatory elements and gene activity. Application to leukemias and cell lines uncovered SV outcomes at several loci, including dysregulated cancer-related pathways and mono-allelic oncogene expression near SV breakpoints. At the intra-patient level, we identified different yet overlapping subclonal SVs that converge on aberrant Wnt signaling. We also deconvoluted the effects of catastrophic chromosomal rearrangements resulting in oncogenic transcription factor dysregulation. scNOVA directly links SVs to their functional consequences, opening the door for single-cell multiomics of SVs in heterogeneous cell populations.

Abstract MP175: Disruption of the Genome Architecture at the PRRX1 Locus is Associated With the Pathogenesis of LMNA -related Dilated Cardiomyopathy

2020 ◽  
Vol 127 (Suppl_1) ◽  
Author(s):  
Yuan Zhang ◽  
Mohamed Ameen ◽  
Isaac Perea Gil ◽  
Jennifer Arthur ◽  
Alexandra A Gavidia ◽  
...  
Keyword(s):  
Dilated Cardiomyopathy ◽  
Single Cell ◽  
Genome Organization ◽  
Molecular Mechanisms ◽  
Critical Role ◽  
Lamin A ◽  
Candidate Locus ◽  
Gene Encoding ◽  
Gene Dysregulation

Background: LMNA , a gene encoding A-type lamin proteins (abbreviated as lamin A), is one of the most frequently mutated genes in dilated cardiomyopathy (DCM). The molecular mechanisms underlying cardiomyocyte dysfunction in LMNA -related DCM remain elusive, translating to the lack of disease-specific therapies. Lamin A has been shown to play a critical role in genome organization via interactions with the chromatin at specific regions called lamina-associated domains (LADs). However, little is known about whether DCM-causing LMNA mutations rearrange the genome conformation and chromosome accessibility. The overarching goal of this study is to define the role of genome organization in LMNA -related DCM. Methods: LMNA -related DCM was modeled in vitro using cardiomyocytes derived from induced pluripotent stem cells (iPSC-CMs) from DCM patients carrying a frameshift mutation in the LMNA gene (c. 348_349insG; p. K117fs) and isogenic controls. We combined genome-wide single cell functional genomic and epigenomic mapping analyses to define the gene regulation and cis-regulatory interactions in isogenic iPSC-CMs. Results: Single-cell RNA-seq revealed global gene dysregulation in LMNA mutant compared to isogenic control iPSC-CMs. The homeodomain transcription factor PRRX1 was significantly upregulated in mutant cells. We showed that LAD integrity is disrupted at the PRRX1 locus in mutant iPSC-CMs. In agreement, DNA fluorescence in situ hybridization (FISH) revealed that the PRRX1 locus loses peripheral association and relocates towards the transcriptionally active nuclear interior in mutant iPSC-CMs. Correspondingly, single-cell assay for transposase accessible chromatin (ATAC)-seq showed increased chromatin co-accessibility at the PRRX1 locus, providing a plausible explanation for ectopic activation of PRRX1 in LMNA mutant iPSC-CMs. Conclusion: Our data suggest that LMNA haploinsufficiency disrupts the structure of LADs, leading to ectopic promoter interactions and altered gene expression in LMNA -related DCM iPSC-CMs. We identified PRRX1 as a promising candidate locus linking changes in LAD organization with gene dysregulation in LMNA -related DCM.

scholarly journals Technologies to study spatial genome organization: beyond 3C

2019 ◽  
Author(s):  
Nadine Übelmesser ◽  
Argyris Papantonis
Keyword(s):  
Genome Organization ◽  
Nuclear Organization ◽  
Three Dimensional ◽  
Nuclear Space ◽  
Chromosome Conformation ◽  
Novel Variants ◽  
Cell Processes ◽  
Systematic Biases ◽  
And Function ◽  
Spatial Genome Organization

Abstract The way that chromatin is organized in three-dimensional nuclear space is now acknowledged as a factor critical for the major cell processes, like transcription, replication and cell division. Researchers have been armed with new molecular and imaging technologies to study this structure-to-function link of genomes, spearheaded by the introduction of the ‘chromosome conformation capture’ technology more than a decade ago. However, this technology is not without shortcomings, and novel variants and orthogonal approaches are being developed to overcome these. As a result, the field of nuclear organization is constantly fueled by methods of increasing resolution and/or throughput that strive to eliminate systematic biases and increase precision. In this review, we attempt to highlight the most recent advances in technology that promise to provide novel insights on how chromosomes fold and function.

scholarly journals Mapping 3D genome organization relative to nuclear compartments using TSA-Seq as a cytological ruler

2018 ◽  
Vol 217 (11) ◽  
pp. 4025-4048 ◽  
Author(s):  
Yu Chen ◽  
Yang Zhang ◽  
Yuchuan Wang ◽  
Liguo Zhang ◽  
Eva K. Brinkman ◽  
...  
Keyword(s):  
Genome Organization ◽  
Spatial Organization ◽  
Essential Feature ◽  
K562 Cells ◽  
Housekeeping Genes ◽  
Mapping Method ◽  
Spatial Gradient ◽  
Nuclear Speckles ◽  
Nuclear Compartments ◽  
Genome Wide

While nuclear compartmentalization is an essential feature of three-dimensional genome organization, no genomic method exists for measuring chromosome distances to defined nuclear structures. In this study, we describe TSA-Seq, a new mapping method capable of providing a “cytological ruler” for estimating mean chromosomal distances from nuclear speckles genome-wide and for predicting several Mbp chromosome trajectories between nuclear compartments without sophisticated computational modeling. Ensemble-averaged results in K562 cells reveal a clear nuclear lamina to speckle axis correlated with a striking spatial gradient in genome activity. This gradient represents a convolution of multiple spatially separated nuclear domains including two types of transcription “hot zones.” Transcription hot zones protruding furthest into the nuclear interior and positioning deterministically very close to nuclear speckles have higher numbers of total genes, the most highly expressed genes, housekeeping genes, genes with low transcriptional pausing, and super-enhancers. Our results demonstrate the capability of TSA-Seq for genome-wide mapping of nuclear structure and suggest a new model for spatial organization of transcription and gene expression.

scholarly journals Discovering a sparse set of pairwise discriminating features in high-dimensional data

2020 ◽  
Author(s):  
Samuel Melton ◽  
Sharad Ramanathan
Keyword(s):  
Single Cell ◽  
Dimensional Space ◽  
Cell Types ◽  
Dimensional Subspace ◽  
Supplementary Information ◽  
High Dimensional ◽  
Technological Advances ◽  
Data Points ◽  
Low Dimensional ◽  
Sparse Set

Abstract Motivation Recent technological advances produce a wealth of high-dimensional descriptions of biological processes, yet extracting meaningful insight and mechanistic understanding from these data remains challenging. For example, in developmental biology, the dynamics of differentiation can now be mapped quantitatively using single-cell RNA sequencing, yet it is difficult to infer molecular regulators of developmental transitions. Here, we show that discovering informative features in the data is crucial for statistical analysis as well as making experimental predictions. Results We identify features based on their ability to discriminate between clusters of the data points. We define a class of problems in which linear separability of clusters is hidden in a low-dimensional space. We propose an unsupervised method to identify the subset of features that define a low-dimensional subspace in which clustering can be conducted. This is achieved by averaging over discriminators trained on an ensemble of proposed cluster configurations. We then apply our method to single-cell RNA-seq data from mouse gastrulation, and identify 27 key transcription factors (out of 409 total), 18 of which are known to define cell states through their expression levels. In this inferred subspace, we find clear signatures of known cell types that eluded classification prior to discovery of the correct low-dimensional subspace. Availability and implementation https://github.com/smelton/SMD. Supplementary information Supplementary data are available at Bioinformatics online.

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