Differential expression (DE) is commonly used to explore molecular mechanisms of biological conditions. While many studies report significant results between their groups of interest, the degree to ...which results are specific to the question at hand is not generally assessed, potentially leading to inaccurate interpretation. This could be particularly problematic for metaanalysis where replicability across datasets is taken as strong evidence for the existence of a specific, biologically relevant signal, but which instead may arise from recurrence of generic processes. To address this, we developed an approach to predict DE based on an analysis of over 600 studies. A predictor based on empirical prior probability of DE performs very well at this task (mean area under the receiver operating characteristic curve, ∼0.8), indicating that a large fraction of DE hit lists are nonspecific. In contrast, predictors based on attributes such as gene function, mutation rates, or network features perform poorly. Genes associated with sex, the extracellular matrix, the immune system, and stress responses are prominent within the “DE prior.” In a series of control studies, we show that these patterns reflect shared biology rather than technical artifacts or ascertainment biases. Finally, we demonstrate the application of the DE prior to data interpretation in three use cases: (i) breast cancer subtyping, (ii) single-cell genomics of pancreatic islet cells, and (iii) metaanalysis of lung adenocarcinoma and renal transplant rejection transcriptomics. In all cases, we find hallmarks of generic DE, highlighting the need for nuanced interpretation of gene phenotypic associations.
Understanding the organizational logic of neural circuits requires deciphering the biological basis of neuronal diversity and identity, but there is no consensus on how neuron types should be ...defined. We analyzed single-cell transcriptomes of a set of anatomically and physiologically characterized cortical GABAergic neurons and conducted a computational genomic screen for transcriptional profiles that distinguish them from one another. We discovered that cardinal GABAergic neuron types are delineated by a transcriptional architecture that encodes their synaptic communication patterns. This architecture comprises 6 categories of ∼40 gene families, including cell-adhesion molecules, transmitter-modulator receptors, ion channels, signaling proteins, neuropeptides and vesicular release components, and transcription factors. Combinatorial expression of select members across families shapes a multi-layered molecular scaffold along the cell membrane that may customize synaptic connectivity patterns and input-output signaling properties. This molecular genetic framework of neuronal identity integrates cell phenotypes along multiple axes and provides a foundation for discovering and classifying neuron types.
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•Single-cell transcriptome analysis of phenotype characterized GABAergic neurons•Computation screen identifies gene families that distinguish GABA subpopulations•6 gene categories shape physiological input-output connectivity of GABA neurons•Transcription profiles of synaptic communication encapsulate neuronal identity
GABAergic neuron types are distinguished by a transcriptional architecture that encodes their synaptic communication patterns.
Single-cell RNA-sequencing (scRNA-seq) technology provides a new avenue to discover and characterize cell types; however, the experiment-specific technical biases and analytic variability inherent to ...current pipelines may undermine its replicability. Meta-analysis is further hampered by the use of ad hoc naming conventions. Here we demonstrate our replication framework, MetaNeighbor, that quantifies the degree to which cell types replicate across datasets, and enables rapid identification of clusters with high similarity. We first measure the replicability of neuronal identity, comparing results across eight technically and biologically diverse datasets to define best practices for more complex assessments. We then apply this to novel interneuron subtypes, finding that 24/45 subtypes have evidence of replication, which enables the identification of robust candidate marker genes. Across tasks we find that large sets of variably expressed genes can identify replicable cell types with high accuracy, suggesting a general route forward for large-scale evaluation of scRNA-seq data.
Chronic pain is a common and devastating condition that induces well-characterized changes in neurons and microglia. One major unanswered question is why these changes should persist long after the ...precipitating injury has healed. Here, we suggest that some of the longer-lasting consequences of nerve injury may be hidden in the epigenome. Cell sorting and sequencing techniques were used to characterize the spinal cord immune response in a mouse model of chronic neuropathic pain. Infiltration of peripheral myeloid cells was found to be absent, and RNA sequencing (RNA-seq) of central microglia revealed transient gene expression changes in response to nerve ligation. Conversely, examination of microglial enhancers revealed persistent, post-injury alterations in close proximity to transcriptionally regulated genes. Enhancers are regions of open chromatin that define a cell’s transcription factor binding profile. We hypothesize that changes at enhancers may constitute a mechanism by which painful experiences are recorded at a molecular level.
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•We examined the spinal cord immune response in a model of neuropathic pain•No infiltration of peripheral macrophages could be detected•RNA-seq of isolated microglia revealed a transient transcriptional response•ChIP-seq revealed persistent, injury-induced alterations of microglial enhancers
Chronic pain is a devastating condition, the longevity of which is not well understood. Denk et al. examined cell-type-specific microglial responses in a model of chronic pain and propose that some of the longer lasting changes from pain inducing injury may be hidden in the epigenome of these immune cells.
Intrathecal delivery of histone deacetylase inhibitors ameliorates hypersensitivity in models of neuropathic pain. This effect may be mediated at the level of the spinal cord through inhibition of ...HDAC1 function.
Histone deacetylase inhibitors (HDACIs) interfere with the epigenetic process of histone acetylation and are known to have analgesic properties in models of chronic inflammatory pain. The aim of this study was to determine whether these compounds could also affect neuropathic pain. Different class I HDACIs were delivered intrathecally into rat spinal cord in models of traumatic nerve injury and antiretroviral drug–induced peripheral neuropathy (stavudine, d4T). Mechanical and thermal hypersensitivity was attenuated by 40% to 50% as a result of HDACI treatment, but only if started before any insult. The drugs globally increased histone acetylation in the spinal cord, but appeared to have no measurable effects in relevant dorsal root ganglia in this treatment paradigm, suggesting that any potential mechanism should be sought in the central nervous system. Microarray analysis of dorsal cord RNA revealed the signature of the specific compound used (MS-275) and suggested that its main effect was mediated through HDAC1. Taken together, these data support a role for histone acetylation in the emergence of neuropathic pain.
Genetic and environmental variation are key contributors during organism development, but the influence of minor perturbations or noise is difficult to assess. This study focuses on the stochastic ...variation in allele-specific expression that persists through cell divisions in the nine-banded armadillo (Dasypus novemcinctus). We investigated the blood transcriptome of five wild monozygotic quadruplets over time to explore the influence of developmental stochasticity on gene expression. We identify an enduring signal of autosomal allelic variability that distinguishes individuals within a quadruplet despite their genetic similarity. This stochastic allelic variation, akin to X-inactivation but broader, provides insight into non-genetic influences on phenotype. The presence of stochastically canalized allelic signatures represents a novel axis for characterizing organismal variability, complementing traditional approaches based on genetic and environmental factors. We also developed a model to explain the inconsistent penetrance associated with these stochastically canalized allelic expressions. By elucidating mechanisms underlying the persistence of allele-specific expression, we enhance understanding of development's role in shaping organismal diversity.
Dose-limiting toxicities significantly impact the benefit/risk profile of many drugs. Whole genome sequencing (WGS) in patients receiving drugs with dose-limiting toxicities can identify therapeutic ...hypotheses to prevent these toxicities. Chemotherapy-induced peripheral neuropathy (CIPN) is a common dose-limiting neurological toxicity of chemotherapies with no effective approach for prevention.
We conducted a genetic study of time-to-first peripheral neuropathy event using 30× germline WGS data from whole blood samples from 4900 European-ancestry cancer patients in 14 randomized controlled trials. A substantial number of patients in these trials received taxane and platinum-based chemotherapies as part of their treatment regimen, either standard of care or in combination with the PD-L1 inhibitor atezolizumab. The trials spanned several cancers including renal cell carcinoma, triple negative breast cancer, non-small cell lung cancer, small cell lung cancer, bladder cancer, ovarian cancer, and melanoma.
We identified a locus consisting of low-frequency variants in intron 13 of GRID2 associated with time-to-onset of first peripheral neuropathy (PN) indexed by rs17020773 (p = 2.03 × 10
, all patients, p = 6.36 × 10
, taxane treated). Gene-level burden analysis identified rare coding variants associated with increased PN risk in the C-terminus of GPR68 (p = 1.59 × 10
, all patients, p = 3.47 × 10
, taxane treated), a pH-sensitive G-protein coupled receptor (GPCR). The variants driving this signal were found to alter predicted arrestin binding motifs in the C-terminus of GPR68. Analysis of snRNA-seq from human dorsal root ganglia (DRG) indicated that expression of GPR68 was highest in mechano-thermo-sensitive nociceptors.
Our genetic study provides insight into the impact of low-frequency and rare coding genetic variation on PN risk and suggests that further study of GPR68 in sensory neurons may yield a therapeutic hypothesis for prevention of CIPN.
As a fundamental unit of life, the cell has rightfully been the subject of intense investigation throughout the history of biology. Technical innovations now make it possible to assay cellular ...features at genomic scale, yielding breakthroughs in our understanding of the molecular organization of tissues, and even whole organisms. As these data accumulate we will soon be faced with a new challenge: making sense of the plethora of results. Early investigations into the replicability of cell type profiles inferred from single-cell RNA sequencing data have indicated that this is likely to be surprisingly straightforward due to consistent gene co-expression. In this opinion article we discuss the evidence for this claim and its implications for interpreting cell type-specific gene expression.
Single-cell RNA sequencing approaches are vastly increasing in scale, with individual experiments routinely profiling thousands or even hundreds of thousands of cells.
Despite technical limitations associated with low-input sequencing, cell classification through unsupervised clustering is surprisingly replicable across studies. This can be attributed to the intrinsic low dimensionality of cell types dominating the variability seen in expression profiles.
Low dimensionality of expression profiles implies gene co-expression. An exploration of the history of co-expression highlights the perils of making gene-level inferences in light of collinearity, an issue that has previously arisen in cancer subtyping analysis.
Co-expression has been both the saving grace and the original sin of single-cell RNA-seq, enabling sample characterization at the cost of gene-level inference.
•Single-cell RNA-sequencing has been used to profile neural cells in many organisms.•Cell expression clusters are often treated as potential cell types or subtypes.•Cluster validation requires ...multiple strands of evidence.•Mechanistic and evolutionary studies may reveal principles of cell diversity.
Recent technical advances have enabled transcriptomics experiments at an unprecedented scale, and single-cell profiles from neural tissue are accumulating rapidly. There has been considerable effort to use these profiles to understand cell diversity, primarily through unsupervised clustering and differential expression analysis. However, current practices to validate these findings vary. In this review, we describe recent efforts to evaluate clusters from single-cell RNA-sequencing data, and provide a framework for considering current evidence and practices in terms of their capacity to establish principles of cell biology. Single-cell RNA-sequencing has already transformed neuroscience. By facilitating detailed comparative and genetic perturbation analyses, it may provide the tools to uncover fundamental mechanisms of neural diversity throughout the tree of life.
The disruptive impact of the coronavirus disease 2019 (COVID-19) pandemic has been felt by workers around the world, and decidedly even more so for precarious, low-wage, and nontraditional workers. ...Challenges for these workers including low wage rates, a lack of access to benefits and resources, and job insecurity were all pressing issues before COVID-19, but the pandemic has exacerbated existing disparities, while other novel challenges have emerged, further impacting the safety and wellbeing of these workers. Historically, research in the fields of organizational behavior and industrial-organizational psychology has overwhelmingly focused on "white-collar" workers with a corresponding underrepresentation of hourly wage workers, contract workers, and others with nontraditional work arrangements (e.g., gig workers). Not only do people belonging to marginalized groups face a disproportionate share of illness and death associated with crises such as COVID-19, but they also tend to be disproportionately represented in these jobs, many of which were deemed essential during the pandemic. Using an intersectional lens, the present scientific commentary and review highlights research related to these issues and serves as a call to action for research examining the experiences of these underrepresented workers. We argue that the pandemic has necessitated a change in our traditional understanding of precarious work and suggest we leverage existing theoretical frameworks to explore our understanding of the effects of worker status on experiences and outcomes during pandemics. Finally, we provide research-informed recommendations for organizations seeking to improve working conditions and uplift workers of all backgrounds.
What is the significance of this article for the general public?This scientific review calls attention to the need to consider the experiences of underrepresented workers as it relates to the psychology of pandemics and work more broadly. We discuss how different marginalized identities face complex challenges during crises such as the coronavirus disease 2019 (COVID-19) pandemic and offer research-informed recommendations to help organizations and their workers prosper.
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