Cellular senescence is a state of irreversibly arrested proliferation, often induced by genotoxic stress 1. Senescent cells participate in a variety of physiological and pathological conditions, ...including tumor suppression 2, embryonic development 3, 4, tissue repair 5–8, and organismal aging 9. The senescence program is variably characterized by several non-exclusive markers, including constitutive DNA damage response (DDR) signaling, senescence-associated β-galactosidase (SA-βgal) activity, increased expression of the cyclin-dependent kinase (CDK) inhibitors p16INK4A (CDKN2A) and p21CIP1 (CDKN1A), increased secretion of many bio-active factors (the senescence-associated secretory phenotype, or SASP), and reduced expression of the nuclear lamina protein LaminB1 (LMNB1) 1. Many senescence-associated markers result from altered transcription, but the senescent phenotype is variable, and methods for clearly identifying senescent cells are lacking 10. Here, we characterize the heterogeneity of the senescence program using numerous whole-transcriptome datasets generated by us or publicly available. We identify transcriptome signatures associated with specific senescence-inducing stresses or senescent cell types and identify and validate genes that are commonly differentially regulated. We also show that the senescent phenotype is dynamic, changing at varying intervals after senescence induction. Identifying novel transcriptome signatures to detect any type of senescent cell or to discriminate among diverse senescence programs is an attractive strategy for determining the diverse biological roles of senescent cells and developing specific drug targets.
•The transcriptome of senescent cells is highly heterogeneous•Senescence transcriptome programs depend on the cell type and stress•Gene expression in senescent cells is temporally dynamic•We identified 55 genes at the core of the senescence-associated transcriptome
The phenotype of senescent cells is highly heterogeneous, but reasons for this variability are poorly understood. Hernandez-Segura et al. identify senescence transcriptome signatures that are strongly associated with specific stresses and cell types and show that the gene expression profiles of various senescence programs are highly dynamic.
Transcriptome sequencing is a powerful technique to study molecular changes that underlie the differences in physiological conditions and disease progression. A typical question that is posed in such ...studies is finding genes with significant changes between sample groups. In this respect expression variability is regarded as a nuisance factor that is primarily of technical origin and complicates the data analysis. However, it is becoming apparent that the biological variation in gene expression might be an important molecular phenotype that can affect physiological parameters. In this review we explore the recent literature on technical and biological variability in gene expression, sources of expression variability, (epi-)genetic hallmarks, and evolutionary constraints in genes with robust and variable gene expression. We provide an overview of recent findings on effects of external cues, such as diet and aging, on expression variability and on other biological phenomena that can be linked to it. We discuss metrics and tools that were developed for quantification of expression variability and highlight the importance of future studies in this direction. To assist the adoption of expression variability analysis, we also provide a detailed description and computer code, which can easily be utilized by other researchers. We also provide a reanalysis of recently published data to highlight the value of the analysis method.
Abstract
Finding novel biomarkers for human pathologies and predicting clinical outcomes for patients is challenging. This stems from the heterogeneous response of individuals to disease and is ...reflected in the inter-individual variability of gene expression responses that obscures differential gene expression analysis. Here, we developed an alternative approach that could be applied to dissect the disease-associated molecular changes. We define gene ensemble noise as a measure that represents a variance for a collection of genes encoding for either members of known biological pathways or subunits of annotated protein complexes and calculated within an individual. The gene ensemble noise allows for the holistic identification and interpretation of gene expression disbalance on the level of gene networks and systems. By comparing gene expression data from COVID-19, H1N1, and sepsis patients we identified common disturbances in a number of pathways and protein complexes relevant to the sepsis pathology. Among others, these include the mitochondrial respiratory chain complex I and peroxisomes. This suggests a Warburg effect and oxidative stress as common hallmarks of the immune host–pathogen response. Finally, we showed that gene ensemble noise could successfully be applied for the prediction of clinical outcome namely, the mortality of patients. Thus, we conclude that gene ensemble noise represents a promising approach for the investigation of molecular mechanisms of pathology through a prism of alterations in the coherent expression of gene circuits.
The WMI and WLI inbred rats were generated from the stress-prone, and not yet fully inbred, Wistar Kyoto (WKY) strain. These were selected using bi-directional selection for immobility in the forced ...swim test and were then sib-mated for over 38 generations. Despite the low level of genetic diversity among WKY progenitors, the WMI substrain is significantly more vulnerable to stress relative to the counter-selected WLI strain. Here we quantify numbers and classes of genomic sequence variants distinguishing these substrains with the long term goal of uncovering functional and behavioral polymorphism that modulate sensitivity to stress and depression-like phenotypes. DNA from WLI and WMI was sequenced using Illumina xTen, IonTorrent, and 10X Chromium linked-read platforms to obtain a combined coverage of ~ 100X for each strain. We identified 4,296 high quality homozygous SNPs and indels between the WMI and WLI. We detected high impact variants in genes previously implicated in depression (e.g. Gnat2), depression-like behavior (e.g. Prlr, Nlrp1a), other psychiatric disease (e.g. Pou6f2, Kdm5a, Reep3, Wdfy3), and responses to psychological stressors (e.g. Pigr). High coverage sequencing data confirm that the two substrains are nearly coisogenic. Nonetheless, the small number of sequence variants contributes to numerous well characterized differences including depression-like behavior, stress reactivity, and addiction related phenotypes. These selected substrains are an ideal resource for forward and reverse genetic studies using a reduced complexity cross.
Chromosome instability leads to aneuploidy, a state in which cells have abnormal numbers of chromosomes, and is found in two out of three cancers. In a chromosomal instable p53 deficient mouse model ...with accelerated lymphomagenesis, we previously observed whole chromosome copy number changes affecting all lymphoma cells. This suggests that chromosome instability is somehow suppressed in the aneuploid lymphomas or that selection for frequently lost/gained chromosomes out-competes the CIN-imposed mis-segregation.
To distinguish between these explanations and to examine karyotype dynamics in chromosome instable lymphoma, we use a newly developed single-cell whole genome sequencing (scWGS) platform that provides a complete and unbiased overview of copy number variations (CNV) in individual cells. To analyse these scWGS data, we develop AneuFinder, which allows annotation of copy number changes in a fully automated fashion and quantification of CNV heterogeneity between cells. Single-cell sequencing and AneuFinder analysis reveals high levels of copy number heterogeneity in chromosome instability-driven murine T-cell lymphoma samples, indicating ongoing chromosome instability. Application of this technology to human B cell leukaemias reveals different levels of karyotype heterogeneity in these cancers.
Our data show that even though aneuploid tumours select for particular and recurring chromosome combinations, single-cell analysis using AneuFinder reveals copy number heterogeneity. This suggests ongoing chromosome instability that other platforms fail to detect. As chromosome instability might drive tumour evolution, karyotype analysis using single-cell sequencing technology could become an essential tool for cancer treatment stratification.
Cellular metabolism is a tightly controlled process in which the cell adapts fluxes through metabolic pathways in response to changes in nutrient supply. Among the transcription factors that regulate ...gene expression and thereby cause changes in cellular metabolism is the basic leucine-zipper (bZIP) transcription factor CCAAT/enhancer-binding protein alpha (C/EBPα). Protein lysine acetylation is a key post-translational modification (PTM) that integrates cellular metabolic cues with other physiological processes. Here, we show that C/EBPα is acetylated by the lysine acetyl transferase (KAT) p300 and deacetylated by the lysine deacetylase (KDAC) sirtuin1 (SIRT1). SIRT1 is activated in times of energy demand by high levels of nicotinamide adenine dinucleotide (NAD+) and controls mitochondrial biogenesis and function. A hypoacetylated mutant of C/EBPα induces the transcription of mitochondrial genes and results in increased mitochondrial respiration. Our study identifies C/EBPα as a key mediator of SIRT1-controlled adaption of energy homeostasis to changes in nutrient supply.
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•p300 acetylates C/EBPα on several lysines•SIRT1 deacetylates C/EBPα•Hypoacetylated C/EBPα increases mitochondrial function•C/EBPα is a mediator of SIRT1-controlled energy homeostasis
Zaini et al. show that the transcription factor C/EBPα is acetylated by p300 and deacetylated by the lysine deacetylase SIRT1. Hypoacetylated C/EBPα induces the transcription of mitochondrial genes and results in increased mitochondrial respiration. C/EBPα is a key mediator of SIRT1-controlled adaption of energy homeostasis to changes in nutrient supply.
Cardiac hypertrophy accompanies many forms of cardiovascular diseases. The mechanisms behind the development and regulation of cardiac hypertrophy in the human setting are poorly understood, which ...can be partially attributed to the lack of a human cardiomyocyte-based preclinical test system recapitulating features of diseased myocardium. The objective of our study is to determine whether human embryonic stem cell-derived cardiomyocytes (hESC-CMs) subjected to mechanical stretch can be used as an adequate in vitro model for studying molecular mechanisms of cardiac hypertrophy. We show that hESC-CMs subjected to cyclic stretch, which mimics mechanical overload, exhibit essential features of a hypertrophic state on structural, functional, and gene expression levels. The presented hESC-CM stretch approach provides insight into molecular mechanisms behind mechanotransduction and cardiac hypertrophy and lays groundwork for the development of pharmacological approaches as well as for discovering potential circulating biomarkers of cardiac dysfunction.
•Cyclic stretch leads to the changes in hESC-CM size, contractility, and elasticity•hESC-CM stretch results in release of cardiac injury mediators•RNA-seq reveals signaling pathways associated with cardiac hypertrophy•Knockdown of FSTL3 and SP6 genes blunted the hypertrophic response
In this article, Berezikov, van der Meer, and colleagues used stem cell-derived cardiomyocytes to model human cardiac hypertrophy. Their approach provides novel insights into molecular mechanisms behind mechanotransduction and cardiac hypertrophy and lays groundwork for the development of new pharmacological approaches as well as for discovering new potential circulating biomarkers of cardiac dysfunction.
Substance use disorder (SUD) is associated with a cluster of cognitive disturbances that engender vulnerability to ongoing drug seeking and relapse. Two of these endophenotypes-risky decision-making ...and impulsivity-are amplified in individuals with SUD and are augmented by repeated exposure to illicit drugs. Identifying genetic factors underlying variability in these behavioral patterns is critical for early identification, prevention, and treatment of SUD-vulnerable individuals. Here, we compared risky decision-making and different facets of impulsivity between two fully inbred substrains of Lewis rats-LEW/NCrl and LEW/NHsd. We performed whole genome sequencing of both substrains to identify almost all relevant variants. We observed substantial differences in risky decision-making and impulsive behaviors. Relative to LEW/NHsd, the LEW/NCrl substrain accepts higher risk options in a decision-making task and higher rates of premature responses in the differential reinforcement of low rates of responding task. These phenotypic differences were more pronounced in females than males. We defined a total of ∼9,000 polymorphisms between these substrains at 40× whole genome short-read coverage. Roughly half of variants are located within a single 1.5 Mb region of Chromosome 8, but none impact protein-coding regions. In contrast, other variants are widely distributed, and of these, 38 are predicted to cause protein-coding variants. In conclusion, Lewis rat substrains differ significantly in risk-taking and impulsivity and only a small number of easily mapped variants are likely to be causal. Sequencing combined with a reduced complexity cross should enable identification of one or more variants underlying multiple complex addiction-relevant behaviors.
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