scholarly journals Inference of Cell Type Composition from Human Brain Transcriptomic Datasets Illuminates the Effects of Age, Manner of Death, Dissection, and Psychiatric Diagnosis

2016 ◽  
Author(s):  
Megan Hastings Hagenauer ◽  
Anton Schulmann ◽  
Jun Z. Li ◽  
Marquis P. Vawter ◽  
David M. Walsh ◽  
...  
Keyword(s):  
Gene Expression ◽  
Blood Cell ◽  
Cell Types ◽  
Post Mortem ◽  
Cell Type ◽  
Cell Content ◽  
Cell Type Composition ◽  
Type Composition ◽  
Cell Gene Expression ◽  
Cell Gene

AbstractPsychiatric illness is unlikely to arise from pathology occurring uniformly across all cell types in affected brain regions. Despite this, transcriptomic analyses of the human brain have typically been conducted using macro-dissected tissue due to the difficulty of performing single-cell type analyses with donated post-mortem brains. To address this issue statistically, we compiled a database of several thousand transcripts that were specifically-enriched in one of 10 primary cortical cell types in previous publications. Using this database, we predicted the relative cell type composition for 833 human cortical samples using microarray or RNA-Seq data from the Pritzker Consortium (GSE92538) or publicly-available databases (GSE53987, GSE21935, GSE21138, CommonMind Consortium). These predictions were generated by averaging normalized expression levels across transcripts specific to each cell type using our R-packageBrainInABlender(validated and publicly-released:https://github.com/hagenaue/BrainInABlender). Using this method, we found that the principal components of variation in the datasets strongly correlated with the neuron to glia ratio of the samples.This variability was not simply due to dissection – the relative balance of brain cell types appeared to be influenced by a variety of demographic, pre- and post-mortem variables. Prolonged hypoxia around the time of death predicted increased astrocytic and endothelial gene expression, illustrating vascular upregulation. Aging was associated with decreased neuronal gene expression. Red blood cell gene expression was reduced in individuals who died following systemic blood loss. Subjects with Major Depressive Disorder had decreased astrocytic gene expression, mirroring previous morphometric observations. Subjects with Schizophrenia had reduced red blood cell gene expression, resembling the hypofrontality detected in fMRI experiments. Finally, in datasets containing samples with especially variable cell content, we found that controlling for predicted sample cell content while evaluating differential expression improved the detection of previously-identified psychiatric effects. We conclude that accounting for cell type can greatly improve the interpretability of transcriptomic data.

scholarly journals Common gene expression signatures in Parkinson’s disease are driven by changes in cell composition

2019 ◽  
Author(s):  
Gonzalo S. Nido ◽  
Fiona Dick ◽  
Lilah Toker ◽  
Kjell Petersen ◽  
Guido Alves ◽  
...  
Keyword(s):  
Gene Expression ◽  
Differential Gene Expression ◽  
Ribosomal Rna ◽  
Post Mortem ◽  
Cell Type ◽  
Cell Type Composition ◽  
Type Composition ◽  
Gene Expression Signatures ◽  
Differential Gene ◽  
Rna Depletion

AbstractBackgroundThe etiology of Parkinson’s disease (PD) is largely unknown. Genome-wide transcriptomic studies in bulk brain tissue have identified several molecular signatures associated with the disease. While these studies have the potential to shed light into the pathogenesis of PD, they are also limited by two major confounders: RNA post mortem degradation and heterogeneous cell type composition of bulk tissue samples. We performed RNA sequencing following ribosomal RNA depletion in the prefrontal cortex of 49 individuals from two independent case-control cohorts. Using cell-type specific markers, we estimated the cell-type composition for each sample and included this in our analysis models to compensate for the variation in cell-type proportions.ResultsRibosomal RNA depletion results in substantially more even transcript coverage, compared to poly(A) capture, in post mortem tissue. Moreover, we show that cell-type composition is a major confounder of differential gene expression analysis in the PD brain. Correcting for cell-type proportions attenuates numerous transcriptomic signatures that have been previously associated with PD, including vesicle trafficking, synaptic transmission, immune and mitochondrial function. Conversely, pathways related to endoplasmic reticulum, lipid oxidation and unfolded protein response are strengthened and surface as the top differential gene expression signatures in the PD prefrontal cortex.ConclusionsDifferential gene expression signatures in PD bulk brain tissue are significantly confounded by underlying differences in cell-type composition. Modeling cell-type heterogeneity is crucial in order to unveil transcriptomic signatures that represent regulatory changes in the PD brain and are, therefore, more likely to be associated with underlying disease mechanisms.

scholarly journals Single Cell Transcriptional Signatures of the Human Placenta in Term and Preterm Parturition

2019 ◽  
Author(s):  
Roger Pique-Regi ◽  
Roberto Romero ◽  
Adi L.Tarca ◽  
Edward D. Sendler ◽  
Yi Xu ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cell ◽  
Single Cell ◽  
Human Placenta ◽  
Preterm Labor ◽  
Cell Types ◽  
Cell Type ◽  
Cell Type Composition ◽  
Type Composition ◽  
Activated T Cell

AbstractMore than 135 million births occur each year; yet, the molecular underpinnings of human parturition in gestational tissues, and in particular the placenta, are still poorly understood. The placenta is a complex heterogeneous organ including cells of both maternal and fetal origin, and insults that disrupt the maternal-fetal dialogue could result in adverse pregnancy outcomes such as preterm birth. There is limited knowledge of the cell type composition and transcriptional activity of the placenta and its compartments during physiologic and pathologic parturition. To fill this knowledge gap, we used scRNA-seq to profile the placental villous tree, basal plate, and chorioamniotic membranes of women with or without labor at term and those with preterm labor. Significant differences in cell type composition and transcriptional profiles were found among placental compartments and across study groups. For the first time, two cell types were identified: 1) lymphatic endothelial decidual cells in the chorioamniotic membranes, and 2) non-proliferative interstitial cytotrophoblasts in the placental villi. Maternal macrophages from the chorioamniotic membranes displayed the largest differences in gene expression (e.g. NFKB1) in both processes of labor; yet, specific gene expression changes were also detected in preterm labor. Importantly, several placental scRNA-seq transcriptional signatures were modulated with advancing gestation in the maternal circulation, and specific immune cell type signatures were increased with labor at term (NK-cell and activated T-cell) and with preterm labor (macrophage, monocyte, and activated T-cell). Herein, we provide a catalogue of cell types and transcriptional profiles in the human placenta, shedding light on the molecular underpinnings and non-invasive prediction of the physiologic and pathologic parturition.One sentence summaryThe common molecular pathway of parturition for both term and preterm spontaneous labor is characterized using single cell gene expression analysis of the human placenta.

scholarly journals Feature extraction approach in single-cell gene expression profiling for cell-type marker identification

2019 ◽  
Author(s):  
Nigatu A. Adossa ◽  
Leif Schauser ◽  
Vivi G. Gregersen ◽  
Laura L. Elo
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Cell Types ◽  
Type I ◽  
Rna Seq ◽  
Cell Type ◽  
Cell Gene Expression ◽  
Cell Type Specific ◽  
Cell Gene ◽  
Marker Identification

AbstractBackgroundRecent advances in single-cell gene expression profiling technology have revolutionized the understanding of molecular processes underlying developmental cell and tissue differentiation, enabling the discovery of novel cell-types and molecular markers that characterize developmental trajectories. Common approaches for identifying marker genes are based on pairwise statistical testing for differential gene expression between cell-types in heterogeneous cell populations, which is challenging due to unequal sample sizes and variance between groups resulting in little statistical power and inflated type I errors.ResultsWe developed an alternative feature extraction method, Marker gene Identification for Cell-type Identity (MICTI) that encodes the cell-type specific expression information to each gene in every single-cell. This approach identifies features (genes) that are cell-type specific for a given cell-type in heterogeneous cell population. To validate this approach, we used (i) simulated single cell RNA-seq data, (ii) human pancreatic islet single-cell RNA-seq data and (iii) a simulated mixture of human single-cell RNA-seq data related to immune cells, particularly B cells, CD4+ memory cells, CD8+ memory cells, dendritic cells, fibroblast cells, and lymphoblast cells. For all cases, we were able to identify established cell-type-specific markers.ConclusionsOur approach represents a highly efficient and fast method as an alternative to differential expression analysis for molecular marker identification in heterogeneous single-cell RNA-seq data.

scholarly journals DOP04 Single cell RNA sequencing identifies distinct intestinal inflammation patterns between primary sclerosing cholangitis-associated colitis and Ulcerative Colitis

2021 ◽  
Vol 15 (Supplement_1) ◽  
pp. S043-S043
Author(s):  
W Uniken Venema ◽  
A Bangma ◽  
M Van der Wijst ◽  
G Kats-Ugurlu ◽  
J Bjork ◽  
...  
Keyword(s):  
Gene Expression ◽  
Ulcerative Colitis ◽  
Sclerosing Cholangitis ◽  
Intestinal Inflammation ◽  
Cell Types ◽  
Cell Type ◽  
Cell Type Composition ◽  
Type Composition ◽  
Distinct Cell ◽  
Single Cell Rna Sequencing

Abstract Background Primary sclerosing cholangitis (PSC) is an inflammatory disorder of the bile ducts. The etiology of PSC is unknown, but it is hypothesized that intestinal barrier dysfunction, as seen in inflammatory bowel disease (IBD), plays a role. Roughly 75% of PSC patients have concomitant IBD (PSC-IBD). PSC-IBD is phenotypically different from ulcerative colitis (UC) with predominantly right-sided disease and a higher risk for colorectal cancer. In this study we aim aim to find probable distinct pathomechanisms for PSC-IBD, by comparing gut mucosal biopsies between PSC-IBD and UC using single-cell RNA sequencing. Methods 47 gut mucosal samples from the colon of subjects with either PSC-IBD (n=24), UC (n=18) or non-IBD control (n=5) were collected, from which 28 were paired inflamed and non-inflamed. Whole biopsies were cryopreserved and dissociated into single cells using collagenase digestion. Library preparation was done using the 10x Genomics system and subsequent sequencing was performed on an MGI2000 sequencer. The ‘Seurat’ R package was used for analysis. Results A total of 75.078 high quality cells identified 38 distinct cell types. No differences in cell type composition were observed between PSC-IBD and UC. We did see different cell type composition and gene expression between inflamed and non-inflamed samples. For example, in PSC-IBD specifically, an enterocyte subtype defined by DUOX2-expression showed inflammatory pathways upon inflammation. UC inflammation, on the other hand, was characterized by involvement of BEST4+ enterocytes and inflammatory fibroblasts. In addition, activated B cells and IgA plasma cells expressed stress-related genes in PSC, but not in UC inflammation. Conclusion We show that intestinal inflammation in PSC-IBD is characterized by distinct, cell-specific gene expression patterns as compared to UC. This highlights differential cell types mediating inflammation between these IBDs. Our study provides insight in cellular mechanisms underlying intestinal disease in PSC, and may serve as a starting point for further studies, for example on the functions of DUOX2+ enterocytes.

scholarly journals Single-cell gene expression of the bovine blastocyst

Reproduction ◽  
2017 ◽  
Vol 154 (5) ◽  
pp. 627-644 ◽  
Author(s):  
Verónica M Negrón-Pérez ◽  
Yanping Zhang ◽  
Peter J Hansen
Keyword(s):  
Gene Expression ◽  
Cell Lineage ◽  
Transcript Abundance ◽  
Cell Types ◽  
Cell Type ◽  
Clade B ◽  
Cell Gene Expression ◽  
Lineage Markers ◽  
Cell Gene ◽  
Bovine Blastocyst

The first two differentiation events in the embryo result in three cell types – epiblast, trophectoderm (TE) and hypoblast. The purpose here was to identify molecular markers for each cell type in the bovine and evaluate the differences in gene expression among individual cells of each lineage. The cDNA from 67 individual cells of dissociated blastocysts was used to determine transcript abundance for 93 genes implicated as cell lineage markers in other species or potentially involved in developmental processes. Clustering analysis indicated that the cells belonged to two major populations (clades A and B) with two subpopulations of clade A and four of clade B. Use of lineage-specific markers from other species indicated that the two subpopulations of clade A represented epiblast and hypoblast respectively while the four subpopulations of clade B were TE. Among the genes upregulated in epiblast were AJAP1, DNMT3A, FGF4, H2AFZ, KDM2B, NANOG, POU5F1, SAV1 and SLIT2. Genes overexpressed in hypoblast included ALPL, FGFR2, FN1, GATA6, GJA1, HDAC1, MBNL3, PDGFRA and SOX17, while genes overexpressed in all four TE populations were ACTA2, CDX2, CYP11A1, GATA2, GATA3, IFNT, KRT8, RAC1 and SFN. The subpopulations of TE varied among each other for multiple genes including the prototypical TE marker IFNT. New markers for each cell type in the bovine blastocyst were identified. Results also indicate heterogeneity in gene expression among TE cells. Further studies are needed to confirm whether subpopulations of TE cells represent different stages in the development of a committed TE phenotype.

scholarly journals Single cell transcriptional signatures of the human placenta in term and preterm parturition

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Roger Pique-Regi ◽  
Roberto Romero ◽  
Adi L Tarca ◽  
Edward D Sendler ◽  
Yi Xu ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cell ◽  
Human Placenta ◽  
Preterm Labor ◽  
Cell Types ◽  
Cell Type ◽  
Transcriptional Profiles ◽  
Cell Type Composition ◽  
Type Composition ◽  
Activated T Cell

More than 135 million births occur each year; yet, the molecular underpinnings of human parturition in gestational tissues, and in particular the placenta, are still poorly understood. The placenta is a complex heterogeneous organ including cells of both maternal and fetal origin, and insults that disrupt the maternal-fetal dialogue could result in adverse pregnancy outcomes such as preterm birth. There is limited knowledge of the cell type composition and transcriptional activity of the placenta and its compartments during physiologic and pathologic parturition. To fill this knowledge gap, we used scRNA-seq to profile the placental villous tree, basal plate, and chorioamniotic membranes of women with or without labor at term and those with preterm labor. Significant differences in cell type composition and transcriptional profiles were found among placental compartments and across study groups. For the first time, two cell types were identified: 1) lymphatic endothelial decidual cells in the chorioamniotic membranes, and 2) non-proliferative interstitial cytotrophoblasts in the placental villi. Maternal macrophages from the chorioamniotic membranes displayed the largest differences in gene expression (e.g. NFKB1) in both processes of labor; yet, specific gene expression changes were also detected in preterm labor. Importantly, several placental scRNA-seq transcriptional signatures were modulated with advancing gestation in the maternal circulation, and specific immune cell type signatures were increased with labor at term (NK-cell and activated T-cell signatures) and with preterm labor (macrophage, monocyte, and activated T-cell signatures). Herein, we provide a catalogue of cell types and transcriptional profiles in the human placenta, shedding light on the molecular underpinnings and non-invasive prediction of the physiologic and pathologic parturition.

scholarly journals Peripheral Blood Cell Gene Expression Diagnostic for Identifying Symptomatic Transthyretin Amyloidosis Patients: Male and Female Specific Signatures

Theranostics ◽  
2016 ◽  
Vol 6 (11) ◽  
pp. 1792-1809 ◽  
Author(s):  
Sunil M. Kurian ◽  
Marta Novais ◽  
Thomas Whisenant ◽  
Terri Gelbart ◽  
Joel N. Buxbaum ◽  
...  
Keyword(s):  
Gene Expression ◽  
Blood Cell ◽  
Peripheral Blood ◽  
Peripheral Blood Cell ◽  
Transthyretin Amyloidosis ◽  
Male And Female ◽  
Cell Gene Expression ◽  
Female Specific ◽  
Cell Gene

scholarly journals Seasonal changes in gene expression represent cell-type composition in whole blood

2014 ◽  
Vol 23 (10) ◽  
pp. 2721-2728 ◽  
Author(s):  
S. De Jong ◽  
M. Neeleman ◽  
J. J. Luykx ◽  
M. J. Ten Berg ◽  
E. Strengman ◽  
...  
Keyword(s):  
Gene Expression ◽  
Whole Blood ◽  
Seasonal Changes ◽  
Cell Type ◽  
Cell Type Composition ◽  
Type Composition

scholarly journals Assessing the Contribution of Relative Macrophage Frequencies to Subcutaneous Adipose Tissue

2021 ◽  
Vol 8 ◽  
Author(s):  
Marianthi Kalafati ◽  
Michael Lenz ◽  
Gökhan Ertaylan ◽  
Ilja C. W. Arts ◽  
Chris T. Evelo ◽  
...  
Keyword(s):  
Gene Expression ◽  
Adipose Tissue ◽  
Subcutaneous Adipose Tissue ◽  
Tissue Cell ◽  
Cell Type ◽  
Expression Of Genes ◽  
Cell Type Composition ◽  
Type Composition ◽  
Adipose Tissue Cell ◽  
Subcutaneous Adipose

Background: Macrophages play an important role in regulating adipose tissue function, while their frequencies in adipose tissue vary between individuals. Adipose tissue infiltration by high frequencies of macrophages has been linked to changes in adipokine levels and low-grade inflammation, frequently associated with the progression of obesity. The objective of this project was to assess the contribution of relative macrophage frequencies to the overall subcutaneous adipose tissue gene expression using publicly available datasets.Methods: Seven publicly available microarray gene expression datasets from human subcutaneous adipose tissue biopsies (n = 519) were used together with TissueDecoder to determine the adipose tissue cell-type composition of each sample. We divided the subjects in four groups based on their relative macrophage frequencies. Differential gene expression analysis between the high and low relative macrophage frequencies groups was performed, adjusting for sex and study. Finally, biological processes were identified using pathway enrichment and network analysis.Results: We observed lower frequencies of adipocytes and higher frequencies of adipose stem cells in individuals characterized by high macrophage frequencies. We additionally studied whether, within subcutaneous adipose tissue, interindividual differences in the relative frequencies of macrophages were reflected in transcriptional differences in metabolic and inflammatory pathways. Adipose tissue of individuals with high macrophage frequencies had a higher expression of genes involved in complement activation, chemotaxis, focal adhesion, and oxidative stress. Similarly, we observed a lower expression of genes involved in lipid metabolism, fatty acid synthesis, and oxidation and mitochondrial respiration.Conclusion: We present an approach that combines publicly available subcutaneous adipose tissue gene expression datasets with a deconvolution algorithm to calculate subcutaneous adipose tissue cell-type composition. The results showed the expected increased inflammation gene expression profile accompanied by decreased gene expression in pathways related to lipid metabolism and mitochondrial respiration in subcutaneous adipose tissue in individuals characterized by high macrophage frequencies. This approach demonstrates the hidden strength of reusing publicly available data to gain cell-type-specific insights into adipose tissue function.

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