Analysis of individual cells identifies cell‐to‐cell variability following induction of cellular senescence

Wiley, Christopher D.; Flynn, James M.; Morrissey, Christapher S.; Lebofsky, Ronald; Shuga, Joe; Dong, Xiao; Unger, Marc; Vijg, Jan; Melov, Simon; Campisi, Judith

doi:10.1111/acel.12632

Cited by 201 publications

(189 citation statements)

References 28 publications

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“…Other recent microarray-based studies focused on the expression changes of spliceosomal genes and splicing factors, reporting a decline in the expression of several components of the splicing machinery 16,17,51 , possibly resulting in an increased heterogeneity of isoforms and transcriptional noise 72,73 . When examining the expression activity of major and minor spliceosomal genes and several splicing factors, we observed only a weak downregulation of these genes during aging in any of the investigated human and mouse samples and even a slight upregulation in Nothobranchius furzeri.…”

Section: /16mentioning

confidence: 99%

The landscape of the alternatively spliced transcriptome remains stable during aging across different species and tissues

Sieber

Barth

Marz

2019

Preprint

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Aging is characterized by a decline of cellular homeostasis over time, leading to various severe disorders and death. Alternative splicing is an important regulatory level of gene expression and thus takes on a key role in the maintenance of accurate cell and tissue function. Missplicing of certain genes has already been linked to several age-associated diseases, such as progeria, Alzheimer's disease, Parkinson's disease and cancer. Nevertheless, many studies focus only on transcriptional variations of single genes or the expression changes of spliceosomal genes, coding for the proteins that aggregate to the spliceosomal machinery. Little is known on the general change of present and switching isoforms in different tissues over time. In this descriptive RNA-Seq study, we report differences and commonalities of isoform usage during aging among different tissues within one species and compare changes of alternative splicing among different, evolutionarily distinct species. Although we identified a multitude of differntially spliced genes among different time points, we observed little to no general changes in the transcriptomic landscape of the investigated samples. Although there is undoubtedly considerable influence of specifically spliced genes on certain age-associated processes, this work shows that alternative splicing remains stable for the majority of genes with aging.

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Section: /16mentioning

confidence: 99%

The landscape of the alternatively spliced transcriptome remains stable during aging across different species and tissues

Sieber

Barth

Marz

2019

Preprint

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“…For example, single‐cell or single‐nuclei RNA sequencing could be combined with the cell‐sorting methods above to understand how variance in gene expression between cells changes with age. While such approaches are beginning to be used to study changes in cell composition of tissues during aging in multicellular eukaryotes, to date they have not been applied in yeast to understand individual variation during aging.…”

Section: Application Of Single‐cell Technologies To Aging Yeast Populmentioning

confidence: 99%

Trajectories of Aging: How Systems Biology in Yeast Can Illuminate Mechanisms of Personalized Aging

et al. 2019

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All organisms age, but the extent to which all organisms age the same way remains a fundamental unanswered question in biology. Across species, it is now clear that at least some aspects of aging are highly conserved and are perhaps universal, but other mechanisms of aging are private to individual species or sets of closely related species. Within the same species, however, it has generally been assumed that the molecular mechanisms of aging are largely invariant from one individual to the next. With the development of new tools for studying aging at the individual cell level in budding yeast, recent data has called this assumption into question. There is emerging evidence that individual yeast mother cells may undergo fundamentally different trajectories of aging. Individual trajectories of aging are difficult to study by traditional population level assays, but through the application of systems biology approaches combined with novel microfluidic technologies, it is now possible to observe and study these phenomena in real time. Understanding the spectrum of mechanisms that determine how different individuals age is a necessary step toward the goal of personalized geroscience, where healthy longevity is optimized for each individual.

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“…The importance of this intrinsic variability is increasingly appreciated (Eldar and Elowitz 2010;Pelkmans 2012). Changes in the magnitude of scEV have been associated with development (Wernet et al 2006;Chang et al 2008;Faure et al 2017;Kumar et al 2017), aging (Martinez-Jimenez et al 2017;Wiley et al 2017), and pathological processes (Segerstolpe et al 2016;Azizi et al 2018).…”

Section: Introductionmentioning

confidence: 99%

Extent, heritability, and functional relevance of single cell expression variability in highly homogeneous populations of human cells

Osorio

Zhong

et al. 2019

Preprint

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Because of recent technological developments, single-cell assays such as single-cell RNA sequencing (scRNA-seq) have become much more widely available and have achieved unprecedented resolution in revealing cell heterogeneity. The extent of intrinsic cell-to-cell variability in gene expression, or single cell expression variability (scEV), has thus been increasingly appreciated. However, it remains unclear whether this variability is functionally important and, if so, what its implications are for multi-cellular organisms. We therefore analyzed multiple scRNA-seq data sets from lymphoblastoid cell lines (LCLs), lung airway epithelial cells (LAECs), and dermal fibroblasts (DFs). For each of the three cell types, we estimated scEV in homogeneous populations of cells; we identified 465, 466, and 291 highly variable genes (HVGs), respectively. These HVGs were enriched with specific functions precisely relevant to the cell types, from which the scRNA-seq data used to identify HVGs were generated-e.g., HVGs identified in lymphoblastoid cells were enriched in cytokine signaling pathways, LAECs collagen formation, and DFs keratinization. HVGs were deeply embedded in gene regulatory networks specific to corresponding cell types. We also found that scEV is a heritable trait, partially determined by cell donors' genetic makeups. Furthermore, across genes, especially immune genes, levels of scEV and between-individual variability in gene expression were positively correlated, suggesting a potential link between the two variabilities measured at different organizational levels. Taken together, our results support the "variation is function" hypothesis, which postulates that scEV is required for higher-level system function. Thus, we argue that quantifying and characterizing scEV in relevant cell types may deepen our understating of normal as well as pathological cellular processes.

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Analysis of individual cells identifies cell‐to‐cell variability following induction of cellular senescence

Cited by 201 publications

References 28 publications

The landscape of the alternatively spliced transcriptome remains stable during aging across different species and tissues

The landscape of the alternatively spliced transcriptome remains stable during aging across different species and tissues

Trajectories of Aging: How Systems Biology in Yeast Can Illuminate Mechanisms of Personalized Aging

Extent, heritability, and functional relevance of single cell expression variability in highly homogeneous populations of human cells

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