Age-related loss of gene-to-gene transcriptional coordination among single cells

Levy, Orr; Amit, Guy; Vaknin, Dana; Snir, Tom; Efroni, Sol; Castaldi, Peter J.; Liu, Yang‐Yu; Cohen, Haim Y.; Bashan, Amir

doi:10.1038/s42255-020-00304-4

Cited by 36 publications

(53 citation statements)

References 44 publications

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“…While both increase and decrease in dynamic range with age do occur, here we specifically focused on increases in variance and its effect on the loss of lineage fidelity with age. Accordingly, in single-cell studies, aged cells were shown to have increased transcriptional variability and loss of transcriptional coordination compared to younger cells of the same tissue [Kowalczyk et al, 2015, Martinez-Jimenez et al, 2017, Enge et al, 2017, Levy et al, 2020], suggesting that increase in cellular heterogeneity with age underlies the population-level increases in variances between the individuals we observed. As such, the molecular signals of aging cells may not be fully captured as stereotyped directional changes -rather a large fraction of age-associated changes will be reflected as increases in measured variance in the molecular signal across an aged cohort.…”

Section: Discussionmentioning

confidence: 75%

Epigenetic changes with age primes mammary luminal epithelia for cancer initiation

Sayaman

Miyano

Senapati

et al. 2021

Preprint

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Aging causes molecular changes that manifest as stereotypical phenotypes yet aging-associated diseases progress only in certain individuals. At lineage-specific resolution, we show how stereotyped and variant responses are integrated in mammary epithelia. Age-dependent directional changes in gene expression and DNA methylation (DNAm) occurred almost exclusively in luminal cells and implicated genome organizers SATB1 and CTCF. DNAm changes were robust indicators of aging luminal cells, and were either directly (anti-)correlated with expression changes or served as priming events for subsequent dysregulation, such as demethylation of ESR1-binding regions in DNAm-regulatory CXXC5 in older luminal cells and luminal-subtype cancers. Variance-driven changes in the transcriptome of both luminal and myoepithelial lineages further contributed to age-dependent loss of lineage fidelity. The pathways affected by transcriptomic and DNAm changes during aging are commonly linked with breast cancer, and together with the differential variability found across individuals, influence aging-associated cancer susceptibility in a subtype-specific manner.

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Section: Discussionmentioning

confidence: 75%

Epigenetic changes with age primes mammary luminal epithelia for cancer initiation

Sayaman

Miyano

Senapati

et al. 2021

Preprint

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“…The average of the gene co-expression matrix, is defined as , where a matrix element represents the Spearman correlation between gene i and gene j . These two approaches were recently compared on real transcriptomic data of aging cells 34 . There was a consistent pattern of reduced GCL values in aging cells across different cell types and different organisms.…”

Section: Resultsmentioning

confidence: 99%

“…The GCL is a “top-down” computational method to evaluate the system-wide transcriptional multivariate dependency of genes, without inferring the whole network of pairwise correlations 34 . We refer to a set of M measured cells with N genes as a matrix , where every vector column represents the individual cell , and each element represents the measured expression value of gene i in that cell.…”

Section: Methodsmentioning

confidence: 99%

“…Recently, a ‘top-down’ approach has been introduced to analyze scRNA-seq data by evaluating the global coordination level between genes (named GCL) 34 . Here, following the above-mentioned approaches that focus on the interrelations between genes to detect biological activity, we propose to use the GCL as an indication for the biological origins of the measured cell-to-cell variability.…”

Section: Introductionmentioning

confidence: 99%

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A top-down measure of gene-to-gene coordination for analyzing cell-to-cell variability

Vaknin

Amit

Bashan

2021

Sci Rep

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Recent technological advances, such as single-cell RNA sequencing (scRNA-seq), allow the measurement of gene expression profiles of individual cells. These expression profiles typically exhibit substantial variations even across seemingly homogeneous populations of cells. Two main different sources contribute to this measured variability: actual differences between the biological activity of the cells and technical measurement errors. Analysis of the biological variability may provide information about the underlying gene regulation of the cells, yet distinguishing it from the technical variability is a challenge. Here, we apply a recently developed computational method for measuring the global gene coordination level (GCL) to systematically study the cell-to-cell variability in numerical models of gene regulation. We simulate ‘biological variability’ by introducing heterogeneity in the underlying regulatory dynamic of different cells, while ‘technical variability’ is represented by stochastic measurement noise. We show that the GCL decreases for cohorts of cells with increased ‘biological variability’ only when it is originated from the interactions between the genes. Moreover, we find that the GCL can evaluate and compare—for cohorts with the same cell-to-cell variability—the ratio between the introduced biological and technical variability. Finally, we show that the GCL is robust against spurious correlations that originate from a small sample size or from the compositionality of the data. The presented methodology can be useful for future analysis of high-dimensional ecological and biochemical dynamics.

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“…Measuring transcriptional noise levels through quantifying individual gene transcript levels across cells in single-cell RNA-sequencing ignores that genes do not operate in isolation but instead are connected in gene regulatory networks. In this issue, Levy et al 8 present a clever new measure to cut across the network of interactions among genes and consider their transcriptional interrelationships. The new measure, called global coordination level (GCL), is based on the average multivariate dependency between the expression levels of random subsets of genes in single-cell RNA-seq datasets.…”

Section: Jan Vijgmentioning

confidence: 99%

Loss of gene coordination as a stochastic cause of ageing

Vijg

2020

Nat Metab

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Age-related loss of gene-to-gene transcriptional coordination among single cells

Cited by 36 publications

References 44 publications

Epigenetic changes with age primes mammary luminal epithelia for cancer initiation

Epigenetic changes with age primes mammary luminal epithelia for cancer initiation

A top-down measure of gene-to-gene coordination for analyzing cell-to-cell variability

Loss of gene coordination as a stochastic cause of ageing

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