Single-nucleus and single-cell transcriptomes compared in matched cortical cell types

Bakken, Trygve E.; Hodge, Rebecca D.; Miller, Jeremy A.; Yao, Zizhen; Nguyen, Thuc Nghi; Aevermann, Brian D.; Barkan, Eliza; Bertagnolli, Darren; Casper, Tamara; Dee, Nick; Garren, Emma; Goldy, Jeff; Graybuck, Lucas T.; Kroll, Matthew; Lasken, Roger S.; Lathia, Kanan; Parry, Sheana; Rimorin, Christine; Scheuermann, Richard H.; Schork, Nicholas J.; Shehata, Soraya I.; Tieu, Michael; Phillips, John W.; Bernard, Amy; Smith, Kimberly A.; Zeng, Hongkui; Lein, Ed; Tasic, Bosiljka

doi:10.1371/journal.pone.0209648

Cited by 435 publications

(440 citation statements)

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“…Overall, we detected more uniquely expressed genes in cells than in nuclei (median gene number: PBS‐cells: 1326; PBS‐nuclei: 480; LPS‐cells: 1481; LPS‐nuclei: 470). Consistent with previous findings, our nuclear data showed a higher proportion of reads mapping to intronic regions and a lower percentage of mitochondrial genes (Figure S1a and S1b) (Bakken et al, ; Lake et al, ). In addition, a lower percentage of ribosomal genes was detected in the nuclei (Figure S1c).…”

Section: Resultssupporting

confidence: 92%

“…Nucleus‐enriched genes were only detected in the PBS condition ( Acaca , Spag5 , and Gm17660 ) and with a less stringent cut off (logFC <−1 and FDR < 0.05), six genes were enriched in LPS nuclei ( Acaca , Kazn , Gm17660 , Gm26916 , Mylip , and Vps13a ) (Table S5). Malat1 was more enriched in nuclei (logFC = −0.72 and FDR = 0 [PBS condition], logFC = −0.66 and FDR = 0 [LPS condition; Table S5), in agreement with earlier findings (Bahar Halpern et al, ; Bakken et al, ). Some representative genes, mentioned above, are depicted in Figure f,g.…”

Section: Resultssupporting

confidence: 90%

“…Some studies confirmed a high concordance between nuclear and whole-cell transcriptomes in neurons (Bakken et al, 2018;Lake et al, 2017 Microglia were isolated from adult mouse brain using the protocol as described before . Briefly, the brains were isolated and triturated using a tissue homogenizer.…”

Section: Nuclear and Whole-cell Transcriptomesmentioning

confidence: 74%

“…Some studies confirmed a high concordance between nuclear and whole‐cell transcriptomes in neurons (Bakken et al, ; Lake et al, ). However, the direct comparison between cellular and nuclear transcriptomes of microglia (and other glia) is yet lacking.…”

Section: Introductionmentioning

confidence: 76%

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Transcriptional profiling of microglia; current state of the art and future perspectives

Gerrits

Heng

Boddeke

et al. 2019

Glia

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Microglia are the tissue macrophages of the central nervous system (CNS) and the first to respond to CNS dysfunction and disease. Gene expression profiling of microglia during development, under homeostatic conditions, and in the diseased CNS provided insight in microglia functions and changes thereof. Single‐cell sequencing studies further contributed to our understanding of microglia heterogeneity in relation to age, sex, and CNS disease. Recently, single nucleus gene expression profiling was performed on (frozen) CNS tissue. Transcriptomic profiling of CNS tissues by (single) nucleus RNA‐sequencing has the advantage that it can be applied to archived and well‐stratified frozen specimens. Here, we give an overview of the significant advances recently made in microglia transcriptional profiling. In addition, we present matched cellular and nuclear microglia RNA‐seq datasets we generated from mouse and human CNS tissue to compare cellular versus nuclear transcriptomes from fresh and frozen samples. We demonstrate that microglia can be similarly profiled with cell and nucleus profiling, and importantly also with nuclei isolated from frozen tissue. Nuclear microglia transcriptomes are a reliable proxy for cellular transcriptomes. Importantly, lipopolysaccharide‐induced changes in gene expression were conserved in the nuclear transcriptome. In addition, heterogeneity in microglia observed in fresh samples was similarly detected in frozen nuclei of the same donor. Together, these results show that microglia nuclear RNAs obtained from frozen CNS tissue are a reliable proxy for microglia gene expression and cellular heterogeneity and may prove an effective strategy to study of the role of microglia in neuropathology.

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Section: Resultssupporting

confidence: 92%

Section: Resultssupporting

confidence: 90%

Section: Nuclear and Whole-cell Transcriptomesmentioning

confidence: 74%

Section: Introductionmentioning

confidence: 76%

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Transcriptional profiling of microglia; current state of the art and future perspectives

Gerrits

Heng

Boddeke

et al. 2019

Glia

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“…In many cases, single cells cannot be used (e.g., when starting from frozen tissues) and therefore single nuclei can be an option. In fact, it was evidenced a good correlation among nuclei gene expression and cell gene expression [126,127]. See Table 1 for a comparison of different systems used to collect single cells.…”

Section: Single-cell Isolationmentioning

confidence: 93%

A Single Cell but Many Different Transcripts: A Journey into the World of Long Non-Coding RNAs

Alessio

Bonadio

Buson

et al. 2020

IJMS

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In late 2012 it was evidenced that most of the human genome is transcribed but only a small percentage of the transcripts are translated. This observation supported the importance of non-coding RNAs and it was confirmed in several organisms. The most abundant non-translated transcripts are long non-coding RNAs (lncRNAs). In contrast to protein-coding RNAs, they show a more cell-specific expression. To understand the function of lncRNAs, it is fundamental to investigate in which cells they are preferentially expressed and to detect their subcellular localization. Recent improvements of techniques that localize single RNA molecules in tissues like single-cell RNA sequencing and fluorescence amplification methods have given a considerable boost in the knowledge of the lncRNA functions. In recent years, single-cell transcription variability was associated with non-coding RNA expression, revealing this class of RNAs as important transcripts in the cell lineage specification. The purpose of this review is to collect updated information about lncRNA classification and new findings on their function derived from single-cell analysis. We also retained useful for all researchers to describe the methods available for single-cell analysis and the databases collecting single-cell and lncRNA data. Tables are included to schematize, describe, and compare exposed concepts.Int. J. Mol. Sci. 2020, 21, 302 2 of 32 not achieved by transcription factors (TFs) alone because of their low number (approximately 1500 in mammals [4]) compared to genes to regulate (90% of the genome is transcribed in human [5]). A single TF is estimated to regulate only ten thousand genes according to Chromatin immunoprecipitation and DNA sequencing experiments (ChIp-seq) [6]. Moreover, the involvement of non-coding RNAs in gene expression regulation was evident [7,8]. The evidence that the non-protein coding component of the human genome is actively transcribed and carries out crucial functions limits the importance of coding genes in genome regulation. Non-coding transcripts become one of the stars of modern biology, especially because of their involvement in a wide range of regulatory processes and changed the association of non-coding regions to junk DNA [3].The genome of multicellular eukaryotes is mostly comprised of non-coding DNA (less than 2% of the human genome codes for proteins [9] while 90% of the human genome is transcribed). Non-coding DNA is transcribed into different classes of non-coding RNAs (ncRNAs) that include structural RNAs (rRNAs and tRNAs) and regulatory RNAs [10]. rRNAs and tRNAs are involved in mRNA translation and can be long or short in size. Regulatory RNAs are further divided into three classes: Small, medium, and long non-coding RNAs. Small non-coding RNAs are between 20 and 50 nucleotides long and include microRNAs (miRNAs) that participate in post-transcriptional regulation [11], small interfering RNAs (siRNAs) that are double-stranded RNAs involved in gene silencing through RNA interfering pathway [12], piwi interacting R...

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Single‐Nucleus RNA Sequencing and Spatial Transcriptomics Reveal the Immunological Microenvironment of Cervical Squamous Cell Carcinoma

Lin

Qiu

et al. 2022

Advanced Science

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The effective treatment of advanced cervical cancer remains challenging. Herein, single-nucleus RNA sequencing (snRNA-seq) and SpaTial enhanced resolution omics-sequencing (Stereo-seq) are used to investigate the immunological microenvironment of cervical squamous cell carcinoma (CSCC). The expression levels of most immune suppressive genes in the tumor and inflammation areas of CSCC are not significantly higher than those in the non-cancer samples, except for LGALS9 and IDO1. Stronger signals of CD56 + NK cells and immature dendritic cells are found in the hypermetabolic tumor areas, whereas more eosinophils, immature B cells, and Treg cells are found in the hypometabolic tumor areas. Moreover, a cluster of pro-tumorigenic cancer-associated myofibroblasts (myCAFs) are identified. The myCAFs may support the growth and metastasis of tumors by inhibiting lymphocyte infiltration and remodeling of the tumor extracellular matrix. Furthermore, these myCAFs are associated with poorer survival probability in patients with CSCC, predict resistance to immunotherapy, and might be present in a small fraction (< 30%) of patients with advanced cancer. Immunohistochemistry and multiplex immunofluorescence staining are conducted to validate the spatial distribution and potential function of myCAFs. Collectively, these findings enhance the understanding of the immunological microenvironment of CSCC and shed light on the treatment of advanced CSCC.

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Single-nucleus and single-cell transcriptomes compared in matched cortical cell types

Cited by 435 publications

References 50 publications

Transcriptional profiling of microglia; current state of the art and future perspectives

Transcriptional profiling of microglia; current state of the art and future perspectives

A Single Cell but Many Different Transcripts: A Journey into the World of Long Non-Coding RNAs

Single‐Nucleus RNA Sequencing and Spatial Transcriptomics Reveal the Immunological Microenvironment of Cervical Squamous Cell Carcinoma

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