scholarly journals Comprehensive functional genomic resource and integrative model for the human brain

Science ◽  
2018 ◽  
Vol 362 (6420) ◽  
pp. eaat8464 ◽  
Author(s):  
Daifeng Wang ◽  
Shuang Liu ◽  
Jonathan Warrell ◽  
Hyejung Won ◽  
Xu Shi ◽  
...  
Keyword(s):  
Psychiatric Disorders ◽  
Molecular Mechanisms ◽  
Genome Wide Association Study ◽  
Expression Profiles ◽  
Cell Types ◽  
Adult Brain ◽  
Population Variation ◽  
Integrative Model ◽  
Risk Scores ◽  
Cell Type

Despite progress in defining genetic risk for psychiatric disorders, their molecular mechanisms remain elusive. Addressing this, the PsychENCODE Consortium has generated a comprehensive online resource for the adult brain across 1866 individuals. The PsychENCODE resource contains ~79,000 brain-active enhancers, sets of Hi-C linkages, and topologically associating domains; single-cell expression profiles for many cell types; expression quantitative-trait loci (QTLs); and further QTLs associated with chromatin, splicing, and cell-type proportions. Integration shows that varying cell-type proportions largely account for the cross-population variation in expression (with >88% reconstruction accuracy). It also allows building of a gene regulatory network, linking genome-wide association study variants to genes (e.g., 321 for schizophrenia). We embed this network into an interpretable deep-learning model, which improves disease prediction by ~6-fold versus polygenic risk scores and identifies key genes and pathways in psychiatric disorders.

scholarly journals In-depth transcriptomic analysis of human retina reveals molecular mechanisms underlying diabetic retinopathy

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kolja Becker ◽  
Holger Klein ◽  
Eric Simon ◽  
Coralie Viollet ◽  
Christian Haslinger ◽  
...  
Keyword(s):  
Diabetic Retinopathy ◽  
Rna Sequencing ◽  
Molecular Mechanisms ◽  
Vision Loss ◽  
Ganglion Cells ◽  
Expression Profiles ◽  
Cell Types ◽  
Sequencing Data ◽  
Disease Stages ◽  
Post Transcriptional Regulation

AbstractDiabetic Retinopathy (DR) is among the major global causes for vision loss. With the rise in diabetes prevalence, an increase in DR incidence is expected. Current understanding of both the molecular etiology and pathways involved in the initiation and progression of DR is limited. Via RNA-Sequencing, we analyzed mRNA and miRNA expression profiles of 80 human post-mortem retinal samples from 43 patients diagnosed with various stages of DR. We found differentially expressed transcripts to be predominantly associated with late stage DR and pathways such as hippo and gap junction signaling. A multivariate regression model identified transcripts with progressive changes throughout disease stages, which in turn displayed significant overlap with sphingolipid and cGMP–PKG signaling. Combined analysis of miRNA and mRNA expression further uncovered disease-relevant miRNA/mRNA associations as potential mechanisms of post-transcriptional regulation. Finally, integrating human retinal single cell RNA-Sequencing data revealed a continuous loss of retinal ganglion cells, and Müller cell mediated changes in histidine and β-alanine signaling. While previously considered primarily a vascular disease, attention in DR has shifted to additional mechanisms and cell-types. Our findings offer an unprecedented and unbiased insight into molecular pathways and cell-specific changes in the development of DR, and provide potential avenues for future therapeutic intervention.

scholarly journals Shisa6 mediates cell-type specific regulation of depression in the nucleus accumbens

2021 ◽  
Author(s):  
Hee-Dae Kim ◽  
Jing Wei ◽  
Tanessa Call ◽  
Nicole Teru Quintus ◽  
Alexander J. Summers ◽  
...  
Keyword(s):  
Nucleus Accumbens ◽  
Molecular Mechanisms ◽  
Cell Types ◽  
Current Treatment ◽  
Specific Cell ◽  
Excitatory Synapses ◽  
Cell Type ◽  
Cell Type Specific ◽  
Specific Regulation ◽  
Circuit Function

AbstractDepression is the leading cause of disability and produces enormous health and economic burdens. Current treatment approaches for depression are largely ineffective and leave more than 50% of patients symptomatic, mainly because of non-selective and broad action of antidepressants. Thus, there is an urgent need to design and develop novel therapeutics to treat depression. Given the heterogeneity and complexity of the brain, identification of molecular mechanisms within specific cell-types responsible for producing depression-like behaviors will advance development of therapies. In the reward circuitry, the nucleus accumbens (NAc) is a key brain region of depression pathophysiology, possibly based on differential activity of D1- or D2- medium spiny neurons (MSNs). Here we report a circuit- and cell-type specific molecular target for depression, Shisa6, recently defined as an AMPAR component, which is increased only in D1-MSNs in the NAc of susceptible mice. Using the Ribotag approach, we dissected the transcriptional profile of D1- and D2-MSNs by RNA sequencing following a mouse model of depression, chronic social defeat stress (CSDS). Bioinformatic analyses identified cell-type specific genes that may contribute to the pathogenesis of depression, including Shisa6. We found selective optogenetic activation of the ventral tegmental area (VTA) to NAc circuit increases Shisa6 expression in D1-MSNs. Shisa6 is specifically located in excitatory synapses of D1-MSNs and increases excitability of neurons, which promotes anxiety- and depression-like behaviors in mice. Cell-type and circuit-specific action of Shisa6, which directly modulates excitatory synapses that convey aversive information, identifies the protein as a potential rapid-antidepressant target for aberrant circuit function in depression.

A novel epithelial cell from neonatal rat lung: isolation and differentiated phenotype

1990 ◽  
Vol 259 (6) ◽  
pp. L415-L425 ◽  
Author(s):  
P. E. Roberts ◽  
D. M. Phillips ◽  
J. P. Mather
Keyword(s):  
Epithelial Cell ◽  
Molecular Mechanisms ◽  
Basal Medium ◽  
Fold Increase ◽  
Cell Types ◽  
Cell Number ◽  
Neonatal Rat ◽  
Rat Lung ◽  
Cell Type

A novel epithelial cell from normal neonatal rat lung has been isolated, established, and maintained for multiple passages in the absence of serum, without undergoing crisis or senescence. By careful manipulation of the nutrition/hormonal microenvironment, we have been able to select, from a heterogeneous population, a single epithelial cell type that can maintain highly differentiated features in vitro. This cell type has characteristics of bronchiolar epithelial cells. A clonal line, RL-65, has been selected and observed for greater than 2 yr in continuous culture. It has been characterized by ultrastructural, morphological, and biochemical criteria. The basal medium for this cell line is Ham's F12/Dulbecco's modified Eagle's (DME) medium plus insulin (1 micrograms/ml), human transferrin (10 micrograms/ml), ethanolamine (10(-4) M), phosphoethanolamine (10(-4) M), selenium (2.5 x 10(-8) M), hydrocortisone (2.5 x 10(-7) M), and forskolin (5 microM). The addition of 150 micrograms/ml of bovine pituitary extract to the defined basal medium stimulates a greater than 10-fold increase in cell number and a 50- to 100-fold increase in thymidine incorporation. The addition of retinoic acid results in further enhancement of cell growth and complete inhibition of keratinization. We have demonstrated a strategy that may be applicable to isolating other cell types from the lung and maintaining their differentiated characteristics for long-term culture in vitro. Such a culture system promises to be a useful model in which to study cellular events associated with differentiation and proliferation in the lung and to better understand the molecular mechanisms involved in these events.

scholarly journals Genomic Architecture of Cells in Tissues (GeACT): Study of Human Mid-gestation Fetus

2020 ◽  
Author(s):  
Feng Tian ◽  
Fan Zhou ◽  
Xiang Li ◽  
Wenping Ma ◽  
Honggui Wu ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Single Cell ◽  
Human Cell ◽  
Expression Profiles ◽  
Single Cells ◽  
Cell Types ◽  
List Type ◽  
Cell Type ◽  
Genomic Architecture ◽  
Gene Modules

SummaryBy circumventing cellular heterogeneity, single cell omics have now been widely utilized for cell typing in human tissues, culminating with the undertaking of human cell atlas aimed at characterizing all human cell types. However, more important are the probing of gene regulatory networks, underlying chromatin architecture and critical transcription factors for each cell type. Here we report the Genomic Architecture of Cells in Tissues (GeACT), a comprehensive genomic data base that collectively address the above needs with the goal of understanding the functional genome in action. GeACT was made possible by our novel single-cell RNA-seq (MALBAC-DT) and ATAC-seq (METATAC) methods of high detectability and precision. We exemplified GeACT by first studying representative organs in human mid-gestation fetus. In particular, correlated gene modules (CGMs) are observed and found to be cell-type-dependent. We linked gene expression profiles to the underlying chromatin states, and found the key transcription factors for representative CGMs.HighlightsGenomic Architecture of Cells in Tissues (GeACT) data for human mid-gestation fetusDetermining correlated gene modules (CGMs) in different cell types by MALBAC-DTMeasuring chromatin open regions in single cells with high detectability by METATACIntegrating transcriptomics and chromatin accessibility to reveal key TFs for a CGM

Localization of migraine susceptibility genes in human brain by single-cell RNA sequencing

Cephalalgia ◽  
2018 ◽  
Vol 38 (13) ◽  
pp. 1976-1983 ◽  
Author(s):  
William Renthal
Keyword(s):  
Human Brain ◽  
Single Cell ◽  
Rna Sequencing ◽  
Expression Profiles ◽  
Cell Types ◽  
Susceptibility Genes ◽  
Brain Cell ◽  
Cell Type ◽  
Single Cell Rna Sequencing ◽  
Brain Cell Types

Background Migraine is a debilitating disorder characterized by severe headaches and associated neurological symptoms. A key challenge to understanding migraine has been the cellular complexity of the human brain and the multiple cell types implicated in its pathophysiology. The present study leverages recent advances in single-cell transcriptomics to localize the specific human brain cell types in which putative migraine susceptibility genes are expressed. Methods The cell-type specific expression of both familial and common migraine-associated genes was determined bioinformatically using data from 2,039 individual human brain cells across two published single-cell RNA sequencing datasets. Enrichment of migraine-associated genes was determined for each brain cell type. Results Analysis of single-brain cell RNA sequencing data from five major subtypes of cells in the human cortex (neurons, oligodendrocytes, astrocytes, microglia, and endothelial cells) indicates that over 40% of known migraine-associated genes are enriched in the expression profiles of a specific brain cell type. Further analysis of neuronal migraine-associated genes demonstrated that approximately 70% were significantly enriched in inhibitory neurons and 30% in excitatory neurons. Conclusions This study takes the next step in understanding the human brain cell types in which putative migraine susceptibility genes are expressed. Both familial and common migraine may arise from dysfunction of discrete cell types within the neurovascular unit, and localization of the affected cell type(s) in an individual patient may provide insight into to their susceptibility to migraine.

scholarly journals Simultaneous enumeration of cancer and immune cell types from bulk tumor gene expression data

eLife ◽  
2017 ◽  
Vol 6 ◽  
Author(s):  
Julien Racle ◽  
Kaat de Jonge ◽  
Petra Baumgaertner ◽  
Daniel E Speiser ◽  
David Gfeller
Keyword(s):  
Gene Expression ◽  
Gene Expression Data ◽  
Immune Cell ◽  
Expression Profiles ◽  
Cell Types ◽  
Response To Therapy ◽  
Expression Data ◽  
Cell Type ◽  
Tumor Gene Expression ◽  
Tumor Gene

Immune cells infiltrating tumors can have important impact on tumor progression and response to therapy. We present an efficient algorithm to simultaneously estimate the fraction of cancer and immune cell types from bulk tumor gene expression data. Our method integrates novel gene expression profiles from each major non-malignant cell type found in tumors, renormalization based on cell-type-specific mRNA content, and the ability to consider uncharacterized and possibly highly variable cell types. Feasibility is demonstrated by validation with flow cytometry, immunohistochemistry and single-cell RNA-Seq analyses of human melanoma and colorectal tumor specimens. Altogether, our work not only improves accuracy but also broadens the scope of absolute cell fraction predictions from tumor gene expression data, and provides a unique novel experimental benchmark for immunogenomics analyses in cancer research (http://epic.gfellerlab.org).

scholarly journals Modeling and Visualizing Cell Type Switching

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Ahmadreza Ghaffarizadeh ◽  
Gregory J. Podgorski ◽  
Nicholas S. Flann
Keyword(s):  
Expression Profiles ◽  
Control Cell ◽  
Three Dimensional ◽  
Myeloid Cell ◽  
Cell Types ◽  
State Transitions ◽  
Cell Type ◽  
New Approach ◽  
Gene Expression Noise ◽  
Lineage Trees

Understanding cellular differentiation is critical in explaining development and for taming diseases such as cancer. Differentiation is conventionally represented using bifurcating lineage trees. However, these lineage trees cannot readily capture or quantify all the types of transitions now known to occur between cell types, including transdifferentiation or differentiation off standard paths. This work introduces a new analysis and visualization technique that is capable of representing all possible transitions between cell states compactly, quantitatively, and intuitively. This method considers the regulatory network of transcription factors that control cell type determination and then performs an analysis of network dynamics to identify stable expression profiles and the potential cell types that they represent. A visualization tool calledCellDiff3Dcreates an intuitive three-dimensional graph that shows the overall direction and probability of transitions between all pairs of cell types within a lineage. In this study, the influence of gene expression noise and mutational changes during myeloid cell differentiation are presented as a demonstration of theCellDiff3Dtechnique, a new approach to quantify and envision all possible cell state transitions in any lineage network.

scholarly journals Characterization of primary cilia features reveal cell-type specific variability in in vitro models of osteogenic and chondrogenic differentiation

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e9799
Author(s):  
Priyanka Upadhyai ◽  
Vishal Singh Guleria ◽  
Prajna Udupa
Keyword(s):  
Cell Lines ◽  
Chondrogenic Differentiation ◽  
Primary Cilia ◽  
Molecular Mechanisms ◽  
Current Knowledge ◽  
Cell Types ◽  
Treatment Modalities ◽  
Cell Type ◽  
Cell Type Specific

Primary cilia are non-motile sensory antennae present on most vertebrate cell surfaces. They serve to transduce and integrate diverse external stimuli into functional cellular responses vital for development, differentiation and homeostasis. Ciliary characteristics, such as length, structure and frequency are often tailored to distinct differentiated cell states. Primary cilia are present on a variety of skeletal cell-types and facilitate the assimilation of sensory cues to direct skeletal development and repair. However, there is limited knowledge of ciliary variation in response to the activation of distinct differentiation cascades in different skeletal cell-types. C3H10T1/2, MC3T3-E1 and ATDC5 cells are mesenchymal stem cells, preosteoblast and prechondrocyte cell-lines, respectively. They are commonly employed in numerous in vitro studies, investigating the molecular mechanisms underlying osteoblast and chondrocyte differentiation, skeletal disease and repair. Here we sought to evaluate the primary cilia length and frequencies during osteogenic differentiation in C3H10T1/2 and MC3T3-E1 and chondrogenic differentiation in ATDC5 cells, over a period of 21 days. Our data inform on the presence of stable cilia to orchestrate signaling and dynamic alterations in their features during extended periods of differentiation. Taken together with existing literature these findings reflect the occurrence of not only lineage but cell-type specific variation in ciliary attributes during differentiation. These results extend our current knowledge, shining light on the variabilities in primary cilia features correlated with distinct differentiated cell phenotypes. It may have broader implications in studies using these cell-lines to explore cilia dependent cellular processes and treatment modalities for skeletal disorders centered on cilia modulation.

scholarly journals Decrease of Nibrin expression in chronic hypoxia is associated with hypoxia-induced chemoresistance in medulloblastoma cells

2017 ◽  
Author(s):  
Sophie Cowman ◽  
Yuen Ngan Fan ◽  
Barry Pizer ◽  
Violaine Sée
Keyword(s):  
Dna Damage ◽  
Cell Line ◽  
Induced Resistance ◽  
Brain Tumours ◽  
Molecular Mechanisms ◽  
Chronic Hypoxia ◽  
Acute Hypoxia ◽  
Adult Brain ◽  
Cell Type ◽  
Hypoxic Conditions

AbstractSolid tumours are less oxygenated than normal tissues. This is called tumour hypoxia and leads to resistance to radiotherapy and chemotherapy. The molecular mechanisms underlying such resistance have been investigated in a range of tumour types, including the adult brain tumours glioblastoma, yet little is known for paediatric brain tumours. Medulloblastoma (MB) is the most common malignant brain tumour in children. Here we used a common MB cell line (D283-MED), to investigate the mechanisms of chemo and radio-resistance in MB, comparing to another MB cell line (MEB-Med8A) and to a widely used glioblastoma cell line (U87MG). In D283-MED and U87MG, chronic hypoxia (5 days), but not acute hypoxia (24 h) induced resistance to etoposide and X-ray irradiation. This acquired resistance upon chronic hypoxia was much less pronounced in MEB-Med8A cells. Using a transcriptomic approach in D283-MED cells, we found a large transcriptional remodelling upon long term hypoxia, in particular the expression of a number of genes involved in detection and repair of double strand breaks (DSB) was altered. The levels of Nibrin (NBN) and MRE11, members of the MRN complex (MRE11/Rad50/NBN) responsible for DSB recognition, were significantly down-regulated. This was associated with a reduction of Ataxia Telangiectasia Mutated (ATM) activation by etoposide, indicating a profound dampening of the DNA damage signalling in hypoxic conditions. As a consequence, p53 activation by etoposide was reduced, and cell survival enhanced. Whilst U87MG shared the same dampened p53 activity, upon chemotherapeutic drug treatment in chronic hypoxic conditions, these cells used a different mechanism, independent of the DNA damage pathway. Together our results demonstrate a new mechanism explaining hypoxia-induced resistance involving the alteration of the response to DSB, but also highlight the cell type to cell type diversity and the necessity to take into account the differing tumour genetic make-up when considering re-sensitisation therapeutic protocols.

scholarly journals Bayesian log-normal deconvolution for enhanced in silico microdissection of bulk gene expression data

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Bárbara Andrade Barbosa ◽  
Saskia D. van Asten ◽  
Ji Won Oh ◽  
Arantza Farina-Sarasqueta ◽  
Joanne Verheij ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Data ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Cell Types ◽  
Expression Data ◽  
Cell Type ◽  
Expression Variability ◽  
Variable Nature ◽  
Log Normal

AbstractDeconvolution of bulk gene expression profiles into the cellular components is pivotal to portraying tissue’s complex cellular make-up, such as the tumor microenvironment. However, the inherently variable nature of gene expression requires a comprehensive statistical model and reliable prior knowledge of individual cell types that can be obtained from single-cell RNA sequencing. We introduce BLADE (Bayesian Log-normAl Deconvolution), a unified Bayesian framework to estimate both cellular composition and gene expression profiles for each cell type. Unlike previous comprehensive statistical approaches, BLADE can handle > 20 types of cells due to the efficient variational inference. Throughout an intensive evaluation with > 700 simulated and real datasets, BLADE demonstrated enhanced robustness against gene expression variability and better completeness than conventional methods, in particular, to reconstruct gene expression profiles of each cell type. In summary, BLADE is a powerful tool to unravel heterogeneous cellular activity in complex biological systems from standard bulk gene expression data.

Sign in / Sign up

Export Citation Format

Share Document