Single cell transcriptomics comes of age

Aldridge, Sarah; Teichmann, Sarah A.

doi:10.1038/s41467-020-18158-5

Cited by 261 publications

(171 citation statements)

References 17 publications

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“…Our work complements these approaches with its focus on analyses of 3D cell organization at the level of cellular structures, and on the generation of quantitative measurements in a human-interpretable manner. Taken together, these studies bring a critical missing dimension, i.e., the spatio-temporal component, to the single cell revolution (Aldridge and Teichmann, 2020). Our study furthers this community goal by adding critical tools, data, and analyses that show the importance of studying large populations of cells and embracing their variations to further our understanding of the underlying rules that organize cells.…”

Section: Discussionmentioning

confidence: 99%

Robust integrated intracellular organization of the human iPS cell: where, how much, and how variable

Viana¹,

Chen²,

Knijnenburg³

et al. 2020

Preprint

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SummaryDespite the intimate link between cell organization and function, the principles underlying intracellular organization and the relation between organization, gene expression and phenotype are not well understood. We address this by creating a benchmark for mean cell organization and the natural range of cell-to-cell variation. This benchmark can be used for comparison to other normal or abnormal cell states. To do this, we developed a reproducible microscope imaging pipeline to generate a high-quality dataset of 3D, high-resolution images of over 200,000 live cells from 25 isogenic human induced pluripotent stem cell (hiPSC) lines from the Allen Cell Collection. Each line contains one fluorescently tagged protein, created via endogenous CRISPR/Cas9 gene editing, representing a key cellular structure or organelle. We used these images to develop a new multi-part and generalizable analysis approach of the locations, amounts, and variation of these 25 cellular structures. Taking an integrated approach, we found that both the extent to which a structure’s individual location varied (“stereotypy”) and the extent to which the structure localized relative to all the other cellular structures (“concordance”) were robust to a wide range of cell shape variation, from flatter to taller, smaller to larger, or less to more polarized cells. We also found that these cellular structures varied greatly in how their volumes scaled with cell and nuclear size. These analyses create a data-driven set of quantitative rules for the locations, amounts, and variation of 25 cellular structures within the hiPSC as a normal baseline for cell organization.

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Section: Discussionmentioning

confidence: 99%

Robust integrated intracellular organization of the human iPS cell: where, how much, and how variable

Viana¹,

Chen²,

Knijnenburg³

et al. 2020

Preprint

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“…However, such bulk-level studies average gene expression across millions of cells, merging together diverse and inconsistent cell types, and thus miss genes that are differentially-expressed only in lower-abundance cell types and genes with opposite changes in different cell populations, and can also result in false positives stemming from cell-type-composition changes between samples. Emerging technologies for single-cell transcriptomics 20,21 achieve both cell-type-specificity and reveal disease-associated changes, as demonstrated for Alzheimer’s Disease 22 , Autism Spectrum Disorder 23 , Major Depressive Disorder 24 , and Multiple Sclerosis 25 , but these have not been applied to schizophrenia to date.…”

Section: Introductionmentioning

confidence: 99%

Single-cell dissection of schizophrenia reveals neurodevelopmental-synaptic axis and transcriptional resilience

Ruzicka

Mohammadi

Dávila-Velderrain

et al. 2020

Preprint

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Schizophrenia is a devastating mental disorder with a high societal burden, complex pathophysiology, and diverse genetic and environmental risk factors. Its complexity, polygenicity, and small-effect-size and cell-type-specific contributors have hindered mechanistic elucidation and the search for new therapeutics. Here, we present the first single-cell dissection of schizophrenia, across 500,000+ cells from 48 postmortem human prefrontal cortex samples, including 24 schizophrenia cases and 24 controls. We annotate 20 cell types/states, providing a high-resolution atlas of schizophrenia-altered genes and pathways in each. We find neurons are the most affected cell type, with deep-layer cortico-cortical projection neurons and parvalbumin-expressing inhibitory neurons showing significant transcriptional changes converging on genetically-implicated regions. We discover a novel excitatory-neuron cell-state indicative of transcriptional resilience and enriched in schizophrenia subjects with less-perturbed transcriptional signatures. We identify key trans-acting factors as candidate drivers of observed transcriptional perturbations, including MEF2C, TCF4, SOX5, and SATB2, and map their binding patterns in postmortem human neurons. These factors regulate distinct gene sets underlying fetal neurodevelopment and adult synaptic function, bridging two leading models of schizophrenia pathogenesis. Our results provide the most detailed map to date for mechanistic understanding and therapeutic development in neuropsychiatric disorders.

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“…Over the past decade, experiments have massively expanded in their scale and implementation, due to technological advances resulting in high-throughput methods that are relatively easy to implement. 38 , 39 In parallel, there now exists a wealth of user-friendly and open-source computational pipelines for data analysis. 40 Transcriptional profiling of cells individually has several advantages over “bulk” analyses, including detection of rare cell types; determination of whether differences between samples are due to differences in the frequencies of cell types present or alternatively changes in individual cell phenotype; and exploration of combinatorial patterns of gene expression and differentiation trajectories.…”

Section: Single-cell Transcriptomicsmentioning

confidence: 99%

Application of Single-Cell Approaches to Study Myeloproliferative Neoplasm Biology

Royston

Mead

Psaila

2021

Hematology/Oncology Clinics of North America

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Philadelphia-negative myeloproliferative neoplasms (MPNs) are an excellent tractable disease model of a number of aspects of human cancer biology, including genetic evolution, tissue-associated fibrosis, and cancer stem cells. In this review, we discuss recent insights into MPN biology gained from the application of a number of new single-cell technologies to study human disease, with a specific focus on single-cell genomics, single-cell transcriptomics, and digital pathology.

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Single cell transcriptomics comes of age

Cited by 261 publications

References 17 publications

Robust integrated intracellular organization of the human iPS cell: where, how much, and how variable

Robust integrated intracellular organization of the human iPS cell: where, how much, and how variable

Single-cell dissection of schizophrenia reveals neurodevelopmental-synaptic axis and transcriptional resilience

Application of Single-Cell Approaches to Study Myeloproliferative Neoplasm Biology

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