scholarly journals Transcriptional bursts explain autosomal random monoallelic expression and affect allelic imbalance

2019 ◽  
Author(s):  
Anton J.M. Larsson ◽  
Björn Reinius ◽  
Tina Jacob ◽  
Tim Dalessandri ◽  
Gert-Jan Hendriks ◽  
...  
Keyword(s):  
Allelic Imbalance ◽  
Expression Patterns ◽  
Monoallelic Expression ◽  
Biological Noise ◽  
Burst Frequency ◽  
Large Numbers ◽  
Single Cell Rna Sequencing ◽  
Transcriptional Bursting ◽  
Burst Kinetics ◽  
Shed Light

AbstractTranscriptional bursts render substantial biological noise in cellular transcriptomes. Here, we investigated the theoretical extent of monoallelic expression resulting from transcriptional bursting and how it compared to the amounts of monoallelic expression of autosomal genes observed in single-cell RNA-sequencing (scRNA-seq) data. We found that transcriptional bursting can explain frequent observations of autosomal monoallelic gene expression in cells. Importantly, the burst frequency largely determined the fraction of cells with monoallelic expression, whereas both burst frequency and size contributed to allelic imbalance. Allelic observations deviate from the expected when analysed across heterogeneous groups of cells, suggesting that allelic modelling can provide an unbiased assessment of heterogeneity within cells. Finally, large numbers of cells are required for analyses of allelic imbalance to avoid confounding observations from transcriptional bursting. Altogether, our results shed light on the implications of transcriptional burst kinetics on allelic expression patterns and phenotypic variation between cells.

scholarly journals Transcriptional bursts explain autosomal random monoallelic expression and affect allelic imbalance

2021 ◽  
Vol 17 (3) ◽  
pp. e1008772
Author(s):  
Anton J. M. Larsson ◽  
Christoph Ziegenhain ◽  
Michael Hagemann-Jensen ◽  
Björn Reinius ◽  
Tina Jacob ◽  
...  
Keyword(s):  
Allelic Imbalance ◽  
Burst Size ◽  
Single Cells ◽  
Expression Patterns ◽  
Allelic Expression ◽  
Monoallelic Expression ◽  
Burst Frequency ◽  
Biallelic Expression ◽  
High Consistency ◽  
Transcriptional Bursting

Transcriptional bursts render substantial biological noise in cellular transcriptomes. Here, we investigated the theoretical extent of allelic expression resulting from transcriptional bursting and how it compared to the amount biallelic, monoallelic and allele-biased expression observed in single-cell RNA-sequencing (scRNA-seq) data. We found that transcriptional bursting can explain the allelic expression patterns observed in single cells, including the frequent observations of autosomal monoallelic gene expression. Importantly, we identified that the burst frequency largely determined the fraction of cells with monoallelic expression, whereas the burst size had little effect on monoallelic observations. The high consistency between the bursting model predictions and scRNA-seq observations made it possible to assess the heterogeneity of a group of cells as their deviation in allelic observations from the expected. Finally, both burst frequency and size contributed to allelic imbalance observations and reinforced that studies of allelic imbalance can be confounded from the inherent noise in transcriptional bursting. Altogether, we demonstrate that allele-level transcriptional bursting renders widespread, although predictable, amounts of monoallelic and biallelic expression in single cells and cell populations.

scholarly journals Transcriptional bursting shape autosomal dynamic random monoallelic expression in pre-gastrulation embryos

2020 ◽  
Author(s):  
C H Naik ◽  
D Chandel ◽  
S Mandal ◽  
S Gayen
Keyword(s):  
Monoallelic Expression ◽  
Wide Spread ◽  
Mammalian Development ◽  
Burst Frequency ◽  
Genome Wide ◽  
Allele Specific ◽  
Transcriptional Bursting ◽  
Burst Kinetics ◽  
Cell Expression ◽  
Early Mammalian Development

AbstractRecent years, allele-specific single cell RNA-seq (scRNA-seq) analysis have demonstrated wide-spread dynamic random monoallelic expression of autosomal genes (aRME). However, the origin of dynamic aRME remains poorly understood. It is believed that dynamic aRME is originated from discrete transcriptional burst of two alleles. Here, for the first time, we have profiled genome-wide pattern of dynamic aRME and allele-specific burst kinetics in mouse pre-gastrulation embryos. We found wide-spread dynamic aRME across the different lineages of pre-gastrulation embryos and which is linked to the allelic burst kinetics. Specially, we found that expression level and burst frequency are the key determinants of dynamic aRME. Altogether, our study provides significant insight about the origin of prevalent dynamic aRME and cell to cell expression heterogeneity during the early mammalian development.

scholarly journals Simultaneous Identification of Brain Cell Type and Lineage via Single Cell RNA Sequencing

2021 ◽  
Author(s):  
Donovan J. Anderson ◽  
Florian M. Pauler ◽  
Aaron McKenna ◽  
Jay Shendure ◽  
Simon Hippenmeyer ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Expression Patterns ◽  
Cortical Cell ◽  
Cell Types ◽  
F1 Hybrids ◽  
Mouse Strains ◽  
Monoallelic Expression ◽  
Cell Divisions ◽  
Single Cell Rna Sequencing

ABSTRACTAcquired mutations are sufficiently frequent such that the genome of a single cell offers a record of its history of cell divisions. Among more common somatic genomic alterations are loss of heterozygosity (LOH). Large LOH events are potentially detectable in single cell RNA sequencing (scRNA-seq) datasets as tracts of monoallelic expression for constitutionally heterozygous single nucleotide variants (SNVs) located among contiguous genes. We identified runs of monoallelic expression, consistent with LOH, uniquely distributed throughout the genome in single cell brain cortex transcriptomes of F1 hybrids involving different inbred mouse strains. We then phylogenetically reconstructed single cell lineages and simultaneously identified cell types by corresponding gene expression patterns. Our results are consistent with progenitor cells giving rise to multiple cortical cell types through stereotyped expansion and distinct waves of neurogenesis. Compared to engineered recording systems, LOH events accumulate throughout the genome and across the lifetime of an organism, affording tremendous capacity for encoding lineage information and increasing resolution for later cell divisions. This approach can conceivably be computationally incorporated into scRNA-seq analysis and may be useful for organisms where genetic engineering is prohibitive, such as humans.

scholarly journals Bioinformatics Analysis of Allele Frequencies and Expression Patterns of ACE2, TMPRSS2 and FURIN in Different Populations and Susceptibility to SARS-CoV-2

Genes ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 1041
Author(s):  
Mohammad Tarek ◽  
Hana Abdelzaher ◽  
Firas Kobeissy ◽  
Hassan A. N. El-Fawal ◽  
Mohammed M. Salama ◽  
...  
Keyword(s):  
Immune Response ◽  
Genetic Factors ◽  
Bioinformatics Analysis ◽  
Expression Patterns ◽  
Spike Protein ◽  
Target Cells ◽  
Health Crisis ◽  
Expression Levels ◽  
Different Populations ◽  
Shed Light

The virus responsible for the COVID-19 global health crisis, SARS-CoV-2, has been shown to utilize the ACE2 protein as an entry point to its target cells. The virus has been shown to rely on the actions of TMPRSS2 (a serine protease), as well as FURIN (a peptidase), for the critical priming of its spike protein. It has been postulated that variations in the sequence and expression of SARS-CoV-2’s receptor (ACE2) and the two priming proteases (TMPRSS2 and FURIN) may be critical in contributing to SARS-CoV-2 infectivity. This study aims to examine the different expression levels of FURIN in various tissues and age ranges in light of ACE2 and TMPRSS2 expression levels using the LungMAP database. Furthermore, we retrieved expression quantitative trait loci (eQTLs) of the three genes and their annotation. We analyzed the frequency of the retrieved variants in data from various populations and compared it to the Egyptian population. We highlight FURIN’s potential interplay with the immune response to SARS-CoV-2 and showcase a myriad of variants of the three genes that are differentially expressed across populations. Our findings provide insights into potential genetic factors that impact SARS-CoV-2 infectivity in different populations and shed light on the varying expression patterns of FURIN.

scholarly journals Cryopreservation of microglia enables single-cell RNA sequencing with minimal effects on disease-related gene expression patterns

iScience ◽  
2021 ◽  
Vol 24 (4) ◽  
pp. 102357
Author(s):  
Brenda Morsey ◽  
Meng Niu ◽  
Shetty Ravi Dyavar ◽  
Courtney V. Fletcher ◽  
Benjamin G. Lamberty ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Rna Sequencing ◽  
Expression Patterns ◽  
Gene Expression Patterns ◽  
Related Gene ◽  
Single Cell Rna Sequencing ◽  
Disease Related Gene

scholarly journals Transcriptional bursting explains the noise-versus-mean relationship in mRNA and protein levels

2016 ◽  
Author(s):  
Roy D. Dar ◽  
Sydney M. Schaffer ◽  
Siddarth S. Dey ◽  
Jonathan E. Foley ◽  
Abhyudai Singh ◽  
...  
Keyword(s):  
Conflict Of Interest ◽  
Burst Size ◽  
Inverse Correlation ◽  
Recent Analysis ◽  
Mrna Levels ◽  
Burst Frequency ◽  
Expression Variability ◽  
Protein Levels ◽  
Transcriptional Bursting ◽  
Cell Expression

Recent analysis (Dey et al, 2015), demonstrates that the HIV-1 Long Terminal Repeat (HIV LTR) promoter exhibits a range of possible transcriptional burst sizes and frequencies for any mean-expression level. However, these results have also been interpreted as demonstrating that cell-to-cell expression variability (noise) and mean are uncorrelated, a significant deviation from previous results. Here, we re-examine the available mRNA and protein abundance data for the HIV LTR and find that noise in mRNA and protein expression scales inversely with the mean along analytically predicted transcriptional burst-size manifolds. We then experimentally perturb transcriptional activity to test a prediction of the multiple burst-size model: that increasing burst frequency will cause mRNA noise to decrease along given burst-size lines as mRNA levels increase. The data show that mRNA and protein noise decrease as mean expression increases, supporting the canonical inverse correlation between noise and mean.Conflict of InterestThe authors declare that they have no conflict of interest.

scholarly journals Super-cells untangle large and complex single-cell transcriptome networks

2021 ◽  
Author(s):  
Mariia Bilous ◽  
Loc Tran ◽  
Chiara Cianciaruso ◽  
Santiago J Carmona ◽  
Mikael J Pittet ◽  
...  
Keyword(s):  
Single Cell ◽  
Coarse Graining ◽  
Cell Populations ◽  
Cell Type ◽  
Large Numbers ◽  
Single Cell Rna Sequencing ◽  
Gene Correlation ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome

Single-cell RNA sequencing (scRNA-seq) technologies offer unique opportunities for exploring heterogeneous cell populations. However, in-depth single-cell transcriptomic characterization of complex tissues often requires profiling tens to hundreds of thousands of cells. Such large numbers of cells represent an important hurdle for downstream analyses, interpretation and visualization. Here we develop a network-based coarse-graining framework where highly similar cells are merged into super-cells. We demonstrate that super-cells not only preserve but often improve the results of downstream analyses including visualization, clustering, differential expression, cell type annotation, gene correlation, imputation, RNA velocity and data integration. By capitalizing on the redundancy inherent to scRNA-seq data, super-cells significantly facilitate and accelerate the construction and interpretation of single-cell atlases, as demonstrated by the integration of 1.46 million cells from COVID-19 patients in less than two hours on a standard desktop.

scholarly journals RECENT RESEARCH ON THE GROWTH PLATE: Recent insights into the regulation of the growth plate

2014 ◽  
Vol 53 (1) ◽  
pp. T1-T9 ◽  
Author(s):  
Julian C Lui ◽  
Ola Nilsson ◽  
Jeffrey Baron
Keyword(s):  
Growth Plate ◽  
Bone Morphogenetic Proteins ◽  
Bone Growth ◽  
Association Studies ◽  
Expression Patterns ◽  
Human Growth ◽  
Cytokine Signaling ◽  
Genome Wide Association Studies ◽  
Paracrine Factors ◽  
Large Numbers

For most bones, elongation is driven primarily by chondrogenesis at the growth plates. This process results from chondrocyte proliferation, hypertrophy, and extracellular matrix secretion, and it is carefully orchestrated by complex networks of local paracrine factors and modulated by endocrine factors. We review here recent advances in the understanding of growth plate physiology. These advances include new approaches to study expression patterns of large numbers of genes in the growth plate, using microdissection followed by microarray. This approach has been combined with genome-wide association studies to provide insights into the regulation of the human growth plate. We also review recent studies elucidating the roles of bone morphogenetic proteins, fibroblast growth factors, C-type natriuretic peptide, and suppressor of cytokine signaling in the local regulation of growth plate chondrogenesis and longitudinal bone growth.

scholarly journals Single-Cell RNA Sequencing Unveils Unique Transcriptomic Signatures of Organ-Specific Endothelial Cells

Circulation ◽  
2020 ◽  
Vol 142 (19) ◽  
pp. 1848-1862 ◽  
Author(s):  
David T. Paik ◽  
Lei Tian ◽  
Ian M. Williams ◽  
Siyeon Rhee ◽  
Hao Zhang ◽  
...  
Keyword(s):  
Endothelial Cells ◽  
Single Cell ◽  
Rna Sequencing ◽  
Expression Patterns ◽  
Receptor Expression ◽  
Transcriptional Networks ◽  
Sequencing Data ◽  
Tissue Specific ◽  
Functional Relationships ◽  
Single Cell Rna Sequencing

Background: Endothelial cells (ECs) display considerable functional heterogeneity depending on the vessel and tissue in which they are located. Whereas these functional differences are presumably imprinted in the transcriptome, the pathways and networks that sustain EC heterogeneity have not been fully delineated. Methods: To investigate the transcriptomic basis of EC specificity, we analyzed single-cell RNA sequencing data from tissue-specific mouse ECs generated by the Tabula Muris consortium. We used a number of bioinformatics tools to uncover markers and sources of EC heterogeneity from single-cell RNA sequencing data. Results: We found a strong correlation between tissue-specific EC transcriptomic measurements generated by either single-cell RNA sequencing or bulk RNA sequencing, thus validating the approach. Using a graph-based clustering algorithm, we found that certain tissue-specific ECs cluster strongly by tissue (eg, liver, brain), whereas others (ie, adipose, heart) have considerable transcriptomic overlap with ECs from other tissues. We identified novel markers of tissue-specific ECs and signaling pathways that may be involved in maintaining their identity. Sex was a considerable source of heterogeneity in the endothelial transcriptome and we discovered Lars2 to be a gene that is highly enriched in ECs from male mice. We found that markers of heart and lung ECs in mice were conserved in human fetal heart and lung ECs. We identified potential angiocrine interactions between tissue-specific ECs and other cell types by analyzing ligand and receptor expression patterns. Conclusions: We used single-cell RNA sequencing data generated by the Tabula Muris consortium to uncover transcriptional networks that maintain tissue-specific EC identity and to identify novel angiocrine and functional relationships between tissue-specific ECs.

scholarly journals Genome-Wide Analysis of Allele-Specific Expression Patterns in Seventeen Tissues of Korean Cattle (Hanwoo)

Animals ◽  
2019 ◽  
Vol 9 (10) ◽  
pp. 727
Author(s):  
Kyu-Sang Lim ◽  
Sun-Sik Chang ◽  
Bong-Hwan Choi ◽  
Seung-Hwan Lee ◽  
Kyung-Tai Lee ◽  
...  
Keyword(s):  
Phenotypic Variation ◽  
Expression Patterns ◽  
Monoallelic Expression ◽  
Specific Expression ◽  
Adult Cattle ◽  
Korean Cattle ◽  
Family Trio ◽  
Epigenetic Effects ◽  
Genome Wide ◽  
Allele Specific

The functional hemizygosity could be caused by the MAE of a given gene and it can be one of the sources to affect the phenotypic variation in cattle. We aimed to identify MAE genes across the transcriptome in Korean cattle (Hanwoo). For three Hanwoo family trios, the transcriptome data of 17 tissues were generated in three offspring. Sixty-two MAE genes had a monoallelic expression in at least one tissue. Comparing genotypes among each family trio, the preferred alleles of 18 genes were identified (maternal expression, n = 9; paternal expression, n = 9). The MAE genes are involved in gene regulation, metabolic processes, and immune responses, and in particular, six genes encode transcription factors (FOXD2, FOXM1, HTATSF1, SCRT1, NKX6-2, and UBN1) with tissue-specific expression. In this study, we report genome-wide MAE genes in seventeen tissues of adult cattle. These results could help to elucidate epigenetic effects on phenotypic variation in Hanwoo.

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