scholarly journals Single-cell replication profiling reveals stochastic regulation of the mammalian replication-timing program

2017 ◽  
Author(s):  
Vishnu Dileep ◽  
David M. Gilbert
Keyword(s):  
Single Cell ◽  
Mammalian Cells ◽  
Replication Timing ◽  
Chromatin Interaction ◽  
Similar Degree ◽  
Cell Replication ◽  
Stochastic Variation ◽  
Cell Cycles ◽  
And Function ◽  
Cell Variation

AbstractIn mammalian cells, distinct replication domains (RDs), corresponding to structural units of chromosomes called topologically-associating domains (TADs), replicate at different times during S-phase1–4. Further, early/late replication of RDs corresponds to active/inactive chromatin interaction compartments5,6. Although replication origins are selected stochastically, such that each cell is using a different cohort of origins to replicate their genomes7–12, replication-timing is regulated independently and upstream of origin selection13 and evidence suggests that replication timing is conserved in consecutive cell cycles14. Hence, quantifying the extent of cell-to-cell variation in replication timing is central to studies of chromosome structure and function. Here we devise a strategy to measure variation in single-cell replication timing using DNA copy number. We find that borders between replicated and un-replicated DNA are highly conserved between cells, demarcating active and inactive compartments of the nucleus. Nonetheless, measurable variation was evident. Surprisingly, we detected a similar degree of variation in replication timing from cell-to-cell, between homologues within cells, and between all domains genome-wide regardless of their replication timing. These results demonstrate that stochastic variation in replication timing is independent of elements that dictate timing or extrinsic environmental variation.

Mapping replication timing domains genome wide in single mammalian cells with single-cell DNA replication sequencing

2020 ◽  
Vol 15 (12) ◽  
pp. 4058-4100
Author(s):  
Hisashi Miura ◽  
Saori Takahashi ◽  
Takahiro Shibata ◽  
Koji Nagao ◽  
Chikashi Obuse ◽  
...  
Keyword(s):  
Dna Replication ◽  
Single Cell ◽  
Mammalian Cells ◽  
Replication Timing ◽  
Genome Wide

scholarly journals Kronos scRT: a uniform framework for single-cell replication timing analysis

2021 ◽  
Author(s):  
Stefano Gnan ◽  
Joseph M. Josephides ◽  
Xia Wu ◽  
Manuela Spagnuolo ◽  
Dalila Saulebekova ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Sorting ◽  
Timing Analysis ◽  
Replication Timing ◽  
Genomic Region ◽  
Cell Replication ◽  
Specific Order ◽  
Mammalian Genomes ◽  
A Cell ◽  
Cell Type Specific

Mammalian genomes are replicated in a cell-type specific order and in coordination with transcription and chromatin organization. Although the field of replication is also entering the single-cell era, current studies require cell sorting, individual cell processing and have yielded a limited number (<100) of cells. Here, we have developed Kronos scRT (https://github.com/CL-CHEN-Lab/Kronos scRT), a software for single-cell Replication Timing (scRT) analysis. Kronos scRT does not require a specific platform nor cell sorting, allowing the investigation of large datasets obtained from asynchronous cells. Analysis of published available data and droplet-based scWGS data generated in the current study, allows exploitation of scRT data from thousands of cells for different mouse and human cell lines. Our results demonstrate that, although most cells replicate within a close timing range for a given genomic region, replication can also occur stochastically throughout S phase. Altogether, Kronos scRT allows investigating the RT program at a single-cell resolution for both homogeneous and heterogeneous cell populations in a fast and comprehensive manner.

scholarly journals Single cell functional genomics reveals the importance of mitochondria in cell-to-cell phenotypic variation

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Riddhiman Dhar ◽  
Alsu M Missarova ◽  
Ben Lehner ◽  
Lucas B Carey
Keyword(s):  
Single Cell ◽  
Stress Tolerance ◽  
Phenotypic Variation ◽  
Mammalian Cells ◽  
Wild Type ◽  
Common Environment ◽  
Automated Microscopy ◽  
Cell Variation ◽  
Anti Fungal ◽  
The Impact

Mutations frequently have outcomes that differ across individuals, even when these individuals are genetically identical and share a common environment. Moreover, individual microbial and mammalian cells can vary substantially in their proliferation rates, stress tolerance, and drug resistance, with important implications for the treatment of infections and cancer. To investigate the causes of cell-to-cell variation in proliferation, we used a high-throughput automated microscopy assay to quantify the impact of deleting >1500 genes in yeast. Mutations affecting mitochondria were particularly variable in their outcome. In both mutant and wild-type cells mitochondrial membrane potential – but not amount – varied substantially across individual cells and predicted cell-to-cell variation in proliferation, mutation outcome, stress tolerance, and resistance to a clinically used anti-fungal drug. These results suggest an important role for cell-to-cell variation in the state of an organelle in single cell phenotypic variation.

scholarly journals A robust and tunable mitotic oscillator in artificial cells

eLife ◽  
2018 ◽  
Vol 7 ◽  
Author(s):  
Ye Guan ◽  
Zhengda Li ◽  
Shiyuan Wang ◽  
Patrick M Barnes ◽  
Xuwen Liu ◽  
...  
Keyword(s):  
Single Cell ◽  
Single Cell Analysis ◽  
Biochemical Networks ◽  
Artificial Cells ◽  
Nuclear Dynamics ◽  
Cell Cycles ◽  
Egg Extracts ◽  
Complex Phenomena ◽  
And Function

Single-cell analysis is pivotal to deciphering complex phenomena like heterogeneity, bistability, and asynchronous oscillations, where a population ensemble cannot represent individual behaviors. Bulk cell-free systems, despite having unique advantages of manipulation and characterization of biochemical networks, lack the essential single-cell information to understand a class of out-of-steady-state dynamics including cell cycles. Here, by encapsulating Xenopus egg extracts in water-in-oil microemulsions, we developed artificial cells that are adjustable in sizes and periods, sustain mitotic oscillations for over 30 cycles, and function in forms from the simplest cytoplasmic-only to the more complicated ones involving nuclear dynamics, mimicking real cells. Such innate flexibility and robustness make it key to studying clock properties like tunability and stochasticity. Our results also highlight energy as an important regulator of cell cycles. We demonstrate a simple, powerful, and likely generalizable strategy of integrating strengths of single-cell approaches into conventional in vitro systems to study complex clock functions.

scholarly journals Multiscale and integrative single-cell Hi-C analysis with Higashi

2020 ◽  
Author(s):  
Ruochi Zhang ◽  
Tianming Zhou ◽  
Jian Ma
Keyword(s):  
Single Cell ◽  
Genome Organization ◽  
Single Cells ◽  
Representation Learning ◽  
3D Genome ◽  
Extensive Evaluation ◽  
Genome Features ◽  
And Function ◽  
Cell Variation ◽  
Cell To Cell Variability

The advent of single-cell Hi-C (scHi-C) technologies offers an unprecedented opportunity to unveil cell-to-cell variability of 3D genome organization. However, the development of computational methods that can effectively enhance scHi-C data quality and extract 3D genome features in single cells remains a major challenge. Here, we report Higashi, a new algorithm that enables robust analysis of scHi-C data based on hypergraph representation learning. Extensive evaluation and integrative analysis demonstrate that Higashi significantly outperforms existing methods for embedding and imputation of scHi-C data. Higashi is uniquely able to reveal multiscale 3D genome features (such as compartmentalization and TAD-like domain boundaries), allowing markedly refined analysis of structure and function connections at single-cell resolution. We show that Higashi can also be applied to the recently developed single-cell co-assays that jointly profile scHi-C and additional epigenomic features. Higashi enables much improved delineation of functionally important cell-to-cell variation of 3D genome organization using scHi-C data.

scholarly journals Single cell functional genomics reveals the importance of mitochondria in cell-to-cell variation in proliferation, drug resistance and mutation outcome

2018 ◽  
Author(s):  
Riddhiman Dhar ◽  
Alsu M Missarova ◽  
Ben Lehner ◽  
Lucas B Carey
Keyword(s):  
Drug Resistance ◽  
Single Cell ◽  
Stress Tolerance ◽  
Mammalian Cells ◽  
Wild Type ◽  
Common Environment ◽  
Automated Microscopy ◽  
Cell Variation ◽  
Anti Fungal ◽  
The Impact

AbstractMutations frequently have outcomes that differ across individuals, even when these individuals are genetically identical and share a common environment. Moreover, individual microbial and mammalian cells can vary substantially in their proliferation rates, stress tolerance, and drug resistance, with important implications for the treatment of infections and cancer. To investigate the causes of cell-to-cell variation in proliferation, we developed a high-throughput automated microscopy assay and used it to quantify the impact of deleting >1,500 genes in yeast. Mutations affecting mitochondria were particularly variable in their outcome. In both mutant and wild-type cells mitochondria state – but not content – varied substantially across individual cells and predicted cell-to-cell variation in proliferation, mutation outcome, stress tolerance, and resistance to a clinically used anti-fungal drug. These results suggest an important role for cell-to-cell variation in the state of an organelle in single cell phenotypic variation.

scholarly journals DNA Replication Timing Enters the Single-Cell Era

Genes ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 221 ◽  
Author(s):  
Ichiro Hiratani ◽  
Saori Takahashi
Keyword(s):  
Dna Replication ◽  
Single Cell ◽  
Cell Population ◽  
Mammalian Cells ◽  
Current Knowledge ◽  
Three Dimensional ◽  
Replication Timing ◽  
3D Genome ◽  
Population Analyses ◽  
Dna Replication Timing

In mammalian cells, DNA replication timing is controlled at the level of megabase (Mb)-sized chromosomal domains and correlates well with transcription, chromatin structure, and three-dimensional (3D) genome organization. Because of these properties, DNA replication timing is an excellent entry point to explore genome regulation at various levels and a variety of studies have been carried out over the years. However, DNA replication timing studies traditionally required at least tens of thousands of cells, and it was unclear whether the replication domains detected by cell population analyses were preserved at the single-cell level. Recently, single-cell DNA replication profiling methods became available, which revealed that the Mb-sized replication domains detected by cell population analyses were actually well preserved in individual cells. In this article, we provide a brief overview of our current knowledge on DNA replication timing regulation in mammals based on cell population studies, outline the findings from single-cell DNA replication profiling, and discuss future directions and challenges.

scholarly journals A yeast-optimized single-cell transcriptomics platform elucidates how mycophenolic acid and guanine alter global mRNA levels

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Guste Urbonaite ◽  
Jimmy Tsz Hang Lee ◽  
Ping Liu ◽  
Guillermo E. Parada ◽  
Martin Hemberg ◽  
...  
Keyword(s):  
Single Cell ◽  
Mycophenolic Acid ◽  
Mammalian Cells ◽  
Yeast Cells ◽  
Mrna Levels ◽  
A Cell ◽  
Size And Morphology ◽  
And Function ◽  
Morphology Characteristics

AbstractStochastic gene expression leads to inherent variability in expression outcomes even in isogenic single-celled organisms grown in the same environment. The Drop-Seq technology facilitates transcriptomic studies of individual mammalian cells, and it has had transformative effects on the characterization of cell identity and function based on single-cell transcript counts. However, application of this technology to organisms with different cell size and morphology characteristics has been challenging. Here we present yeastDrop-Seq, a yeast-optimized platform for quantifying the number of distinct mRNA molecules in a cell-specific manner in individual yeast cells. Using yeastDrop-Seq, we measured the transcriptomic impact of the lifespan-extending compound mycophenolic acid and its epistatic agent guanine. Each treatment condition had a distinct transcriptomic footprint on isogenic yeast cells as indicated by distinct clustering with clear separations among the different groups. The yeastDrop-Seq platform facilitates transcriptomic profiling of yeast cells for basic science and biotechnology applications.

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