scholarly journals Investigating cell cycle-dependent gene expression in the context of nuclear architecture at single-allele resolution

2020 ◽  
Vol 133 (12) ◽  
pp. jcs246330 ◽  
Author(s):  
Shivnarayan Dhuppar ◽  
Aprotim Mazumder
2019 ◽  
Author(s):  
Shivnarayan Dhuppar ◽  
Aprotim Mazumder

AbstractNuclear architecture is the organization of the genome within a cell nucleus with respect to different nuclear landmarks such as nuclear lamina, matrix or nucleoli. Lately it has emerged as a major regulator of gene expression in mammalian cells. The studies connecting nuclear architecture with gene expression are largely population-averaged and do not report on the heterogeneity in genome organization or in gene expression within a population. In this report we present a method for combining 3D DNA Fluorescence in situ Hybridization (FISH) with single molecule RNA FISH (smFISH) and immunofluorescence to study nuclear architecture-dependent gene regulation on a cell-by-cell basis. We further combine it with an imaging-based cell cycle staging to correlate nuclear architecture with gene expression across the cell cycle. We present this in the context of Cyclin A2 (CCNA2) gene for its known cell cycle-dependent expression. We show that, across the cell cycle, the expression of a CCNA2 gene copy is stochastic and depends neither on its sub-nuclear position—which usually lies close to nuclear lamina—nor on the expression from the other copies.


2013 ◽  
Vol 13 (8) ◽  
pp. 585-595 ◽  
Author(s):  
Subhashini Sadasivam ◽  
James A. DeCaprio

2019 ◽  
Vol 116 (39) ◽  
pp. 19490-19499 ◽  
Author(s):  
Chenglong Xia ◽  
Jean Fan ◽  
George Emanuel ◽  
Junjie Hao ◽  
Xiaowei Zhuang

The expression profiles and spatial distributions of RNAs regulate many cellular functions. Image-based transcriptomic approaches provide powerful means to measure both expression and spatial information of RNAs in individual cells within their native environment. Among these approaches, multiplexed error-robust fluorescence in situ hybridization (MERFISH) has achieved spatially resolved RNA quantification at transcriptome scale by massively multiplexing single-molecule FISH measurements. Here, we increased the gene throughput of MERFISH and demonstrated simultaneous measurements of RNA transcripts from ∼10,000 genes in individual cells with ∼80% detection efficiency and ∼4% misidentification rate. We combined MERFISH with cellular structure imaging to determine subcellular compartmentalization of RNAs. We validated this approach by showing enrichment of secretome transcripts at the endoplasmic reticulum, and further revealed enrichment of long noncoding RNAs, RNAs with retained introns, and a subgroup of protein-coding mRNAs in the cell nucleus. Leveraging spatially resolved RNA profiling, we developed an approach to determine RNA velocity in situ using the balance of nuclear versus cytoplasmic RNA counts. We applied this approach to infer pseudotime ordering of cells and identified cells at different cell-cycle states, revealing ∼1,600 genes with putative cell cycle-dependent expression and a gradual transcription profile change as cells progress through cell-cycle stages. Our analysis further revealed cell cycle-dependent and cell cycle-independent spatial heterogeneity of transcriptionally distinct cells. We envision that the ability to perform spatially resolved, genome-wide RNA profiling with high detection efficiency and accuracy by MERFISH could help address a wide array of questions ranging from the regulation of gene expression in cells to the development of cell fate and organization in tissues.


2012 ◽  
Vol 32 (22) ◽  
pp. 4651-4661 ◽  
Author(s):  
Z. Darieva ◽  
N. Han ◽  
S. Warwood ◽  
K. S. Doris ◽  
B. A. Morgan ◽  
...  

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