scholarly journals Cell-type specific analysis of heterogeneous methylation signal using a Bayesian model-based approach

2019 ◽  
Author(s):  
Daniel W Kennedy ◽  
Nicole M White ◽  
Miles C Benton ◽  
Rodney A Lea ◽  
Kerrie Mengersen
Keyword(s):  
Bayesian Model ◽  
A Priori ◽  
Killer Cell ◽  
Cell Types ◽  
Cell Type ◽  
Model Based ◽  
Independent Verification ◽  
Specific Analysis ◽  
Specific Variation ◽  
Cell Type Specific

MotivationEpigenome-wide studies are often performed using heterogeneous methylation samples, especially when there is no prior information as to which cell-types are disease associated. While much work has been done in ascertaining cell-type fractions and removing cell-type heterogeneity variation, relatively little work has been done in identifying cell-type specific variation in heterogeneous samples.ResultsIn this paper, we present a Bayesian model-based approach for making cell-type specific inferences in heterogeneous settings, by using a logit-Normal sampling distribution and incorporating a priori knowledge of cell-type lineage. The method is applied to the detection of cell-type specific sex effects in methylation, where cell-type information is present as an independent verification of the results. Panels derived from this method contained more loci where CD8+T, CD19+B and Natural Killer cell-types were differentially methylated. The analysis suggests that an ensemble approach with this method included could be used for discovering cell-type specific methylation changes.Availabilityhttps://github.com/danwkenn/Bayes_CDM

scholarly journals Cell-type specific analysis of physiological action of estrogen in mouse oviducts

2020 ◽  
Author(s):  
Emily A. McGlade ◽  
Gerardo G. Herrera ◽  
Kalli K. Stephens ◽  
Sierra L. W. Olsen ◽  
Sarayut Winuthayanon ◽  
...  
Keyword(s):  
Hormone Replacement ◽  
Cell Types ◽  
Normal Embryo ◽  
Developmental Defect ◽  
Cell Type ◽  
Specific Analysis ◽  
Cell Type Specific ◽  
17Β Estradiol ◽  
Oviductal Cell

AbstractOne of the endogenous estrogens, 17β-estradiol (E2) is a female steroid hormone secreted from the ovary. It is well established that E2 causes biochemical and histological changes in the uterus. The oviduct response to E2 is virtually unknown in an in vivo environment. In this study, we assessed the effect of E2 on each oviductal cell type, using an ovariectomized-hormone-replacement mouse model, single cell RNA-sequencing (scRNA-seq), in situ hybridization, and cell-type-specific deletion in mice. We found that each cell type in the oviduct responded to E2 distinctively, especially ciliated and secretory epithelial cells. The treatment of exogenous E2 did not drastically alter the transcriptomic profile from that of endogenous E2 produced during estrus. Moreover, we have identified and validated genes of interest in our datasets that may be used as cell- and region-specific markers in the oviduct. Insulin-like growth factor 1 (Igf1) was characterized as an E2-target gene in the mouse oviduct and was also expressed in human Fallopian tubes. Deletion of Igf1 in progesterone receptor (Pgr)-expressing cells resulted in female subfertility, partially due to an embryo developmental defect and embryo retention within the oviduct. In summary, we have shown that oviductal cell types are differentially regulated by E2 and support gene expression changes that are required for normal embryo development and transport in mouse models.

scholarly journals Cell-Type-Specific Proteomics: A Neuroscience Perspective

Proteomes ◽  
2018 ◽  
Vol 6 (4) ◽  
pp. 51 ◽  
Author(s):  
Rashaun S. Wilson ◽  
Angus C. Nairn
Keyword(s):  
Protein Detection ◽  
Analytical Techniques ◽  
Cell Types ◽  
Brain Regions ◽  
Cell Populations ◽  
Specific Cell ◽  
Cell Type ◽  
Specific Analysis ◽  
Cell Type Specific ◽  
Proteomics Research

Cell-type-specific analysis has become a major focus for many investigators in the field of neuroscience, particularly because of the large number of different cell populations found in brain tissue that play roles in a variety of developmental and behavioral disorders. However, isolation of these specific cell types can be challenging due to their nonuniformity and complex projections to different brain regions. Moreover, many analytical techniques used for protein detection and quantitation remain insensitive to the low amounts of protein extracted from specific cell populations. Despite these challenges, methods to improve proteomic yield and increase resolution continue to develop at a rapid rate. In this review, we highlight the importance of cell-type-specific proteomics in neuroscience and the technical difficulties associated. Furthermore, current progress and technological advancements in cell-type-specific proteomics research are discussed with an emphasis in neuroscience.

SCAN-ATAC-Sim: a scalable and efficient method for simulating single-cell ATAC-seq data from bulk-tissue experiments

2020 ◽  
Author(s):  
Zhanlin Chen ◽  
Jing Zhang ◽  
Jason Liu ◽  
Zixuan Zhang ◽  
Jiangqi Zhu ◽  
...  
Keyword(s):  
Signal To Noise Ratio ◽  
A Priori ◽  
Simulation Method ◽  
Cell Types ◽  
Supplementary Information ◽  
Cell Type ◽  
Laptop Computer ◽  
Representative Cell ◽  
Powerful Approach ◽  
Cell Type Specific

AbstractSummaryscATAC-seq is a powerful approach for characterizing cell-type-specific regulatory landscapes. However, it is difficult to benchmark the performance of various scATAC-seq analysis techniques (such as clustering and deconvolution) without having a priori a known set of gold-standard cell types. To simulate scATAC-seq experiments with known cell-type labels, we introduce an efficient and scalable scATAC-seq simulation method (SCAN-ATAC-Sim) that down-samples bulk ATAC-seq data (e.g., from representative cell lines or tissues). Our protocol uses a consistent but tunable signal-to-noise ratio across cell types in a scATAC-seq simulation for integrating bulk experiments with different levels of background noise, and it independently samples twice without replacement to account for the diploid genome. Because it uses an efficient weighted reservoir sampling algorithm and is highly parallelizable with OpenMP, our implementation in C++ allows millions of cells to be simulated in less than an hour on a laptop computer.AvailabilitySCAN-ATAC-Sim is available at scan-atac-sim.gersteinlab.org.Contactpi@gersteinlab.orgSupplementary informationSupplementary data are available at Bioinformatics online.

scholarly journals SCAN-ATAC-Sim: a scalable and efficient method for simulating single-cell ATAC-seq data from bulk-tissue experiments

2021 ◽  
Author(s):  
Zhanlin Chen ◽  
Jing Zhang ◽  
Jason Liu1 ◽  
Zixuan Zhang ◽  
Jiangqi Zhu ◽  
...  
Keyword(s):  
Signal To Noise Ratio ◽  
A Priori ◽  
Simulation Method ◽  
Cell Types ◽  
Supplementary Information ◽  
Cell Type ◽  
Laptop Computer ◽  
Representative Cell ◽  
Powerful Approach ◽  
Cell Type Specific

Abstract Summary scATAC-seq is a powerful approach for characterizing cell-type-specific regulatory landscapes. However, it is difficult to benchmark the performance of various scATAC-seq analysis techniques (such as clustering and deconvolution) without having a priori a known set of gold-standard cell types. To simulate scATAC-seq experiments with known cell-type labels, we introduce an efficient and scalable scATAC-seq simulation method (SCAN-ATAC-Sim) that down-samples bulk ATAC-seq data (e.g., from representative cell lines or tissues). Our protocol uses a consistent but tunable signal-to-noise ratio across cell types in a scATAC-seq simulation for integrating bulk experiments with different levels of background noise, and it independently samples twice without replacement to account for the diploid genome. Because it uses an efficient weighted reservoir sampling algorithm and is highly parallelizable with OpenMP, our implementation in C ++ allows millions of cells to be simulated in less than an hour on a laptop computer. Availability SCAN-ATAC-Sim is available at scan-atac-sim.gersteinlab.org. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Connectivity characterization of the mouse basolateral amygdalar complex

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Houri Hintiryan ◽  
Ian Bowman ◽  
David L. Johnson ◽  
Laura Korobkova ◽  
Muye Zhu ◽  
...  
Keyword(s):  
Granular Cell ◽  
Cell Types ◽  
Projection Neurons ◽  
Cell Type ◽  
Connectivity Map ◽  
Analysis Techniques ◽  
Domain Specific ◽  
Cell Type Specific ◽  
Unique Domain

AbstractThe basolateral amygdalar complex (BLA) is implicated in behaviors ranging from fear acquisition to addiction. Optogenetic methods have enabled the association of circuit-specific functions to uniquely connected BLA cell types. Thus, a systematic and detailed connectivity profile of BLA projection neurons to inform granular, cell type-specific interrogations is warranted. Here, we apply machine-learning based computational and informatics analysis techniques to the results of circuit-tracing experiments to create a foundational, comprehensive BLA connectivity map. The analyses identify three distinct domains within the anterior BLA (BLAa) that house target-specific projection neurons with distinguishable morphological features. We identify brain-wide targets of projection neurons in the three BLAa domains, as well as in the posterior BLA, ventral BLA, posterior basomedial, and lateral amygdalar nuclei. Inputs to each nucleus also are identified via retrograde tracing. The data suggests that connectionally unique, domain-specific BLAa neurons are associated with distinct behavior networks.

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.

scholarly journals Histone modifications form a cell-type-specific chromosomal bar code that persists through the cell cycle

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
John A. Halsall ◽  
Simon Andrews ◽  
Felix Krueger ◽  
Charlotte E. Rutledge ◽  
Gabriella Ficz ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Cycle ◽  
Histone Modifications ◽  
Expression Patterns ◽  
Cell Types ◽  
Cell Type ◽  
Bar Code ◽  
Genes Encoding ◽  
Cell Type Specific ◽  
Rolling Windows

AbstractChromatin configuration influences gene expression in eukaryotes at multiple levels, from individual nucleosomes to chromatin domains several Mb long. Post-translational modifications (PTM) of core histones seem to be involved in chromatin structural transitions, but how remains unclear. To explore this, we used ChIP-seq and two cell types, HeLa and lymphoblastoid (LCL), to define how changes in chromatin packaging through the cell cycle influence the distributions of three transcription-associated histone modifications, H3K9ac, H3K4me3 and H3K27me3. We show that chromosome regions (bands) of 10–50 Mb, detectable by immunofluorescence microscopy of metaphase (M) chromosomes, are also present in G1 and G2. They comprise 1–5 Mb sub-bands that differ between HeLa and LCL but remain consistent through the cell cycle. The same sub-bands are defined by H3K9ac and H3K4me3, while H3K27me3 spreads more widely. We found little change between cell cycle phases, whether compared by 5 Kb rolling windows or when analysis was restricted to functional elements such as transcription start sites and topologically associating domains. Only a small number of genes showed cell-cycle related changes: at genes encoding proteins involved in mitosis, H3K9 became highly acetylated in G2M, possibly because of ongoing transcription. In conclusion, modified histone isoforms H3K9ac, H3K4me3 and H3K27me3 exhibit a characteristic genomic distribution at resolutions of 1 Mb and below that differs between HeLa and lymphoblastoid cells but remains remarkably consistent through the cell cycle. We suggest that this cell-type-specific chromosomal bar-code is part of a homeostatic mechanism by which cells retain their characteristic gene expression patterns, and hence their identity, through multiple mitoses.

scholarly journals An analytical method for the identification of cell type-specific disease gene modules

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Jinting Guan ◽  
Yiping Lin ◽  
Yang Wang ◽  
Junchao Gao ◽  
Guoli Ji
Keyword(s):  
Disease Gene ◽  
Gene Interaction ◽  
Cell Types ◽  
Autism Spectrum ◽  
Specific Gene ◽  
Cell Type ◽  
Specific Disease ◽  
Cell Type Specific ◽  
Gene Modules ◽  
Disease Associated Genes

Abstract Background Genome-wide association studies have identified genetic variants associated with the risk of brain-related diseases, such as neurological and psychiatric disorders, while the causal variants and the specific vulnerable cell types are often needed to be studied. Many disease-associated genes are expressed in multiple cell types of human brains, while the pathologic variants affect primarily specific cell types. We hypothesize a model in which what determines the manifestation of a disease in a cell type is the presence of disease module comprised of disease-associated genes, instead of individual genes. Therefore, it is essential to identify the presence/absence of disease gene modules in cells. Methods To characterize the cell type-specificity of brain-related diseases, we construct human brain cell type-specific gene interaction networks integrating human brain nucleus gene expression data with a referenced tissue-specific gene interaction network. Then from the cell type-specific gene interaction networks, we identify significant cell type-specific disease gene modules by performing statistical tests. Results Between neurons and glia cells, the constructed cell type-specific gene networks and their gene functions are distinct. Then we identify cell type-specific disease gene modules associated with autism spectrum disorder and find that different gene modules are formed and distinct gene functions may be dysregulated in different cells. We also study the similarity and dissimilarity in cell type-specific disease gene modules among autism spectrum disorder, schizophrenia and bipolar disorder. The functions of neurons-specific disease gene modules are associated with synapse for all three diseases, while those in glia cells are different. To facilitate the use of our method, we develop an R package, CtsDGM, for the identification of cell type-specific disease gene modules. Conclusions The results support our hypothesis that a disease manifests itself in a cell type through forming a statistically significant disease gene module. The identification of cell type-specific disease gene modules can promote the development of more targeted biomarkers and treatments for the disease. Our method can be applied for depicting the cell type heterogeneity of a given disease, and also for studying the similarity and dissimilarity between different disorders, providing new insights into the molecular mechanisms underlying the pathogenesis and progression of diseases.

Cytoplasmic, nuclear, membrane-bound and secreted [35S]methionine-labelled polypeptide pattern in differentiating fibroblast stem cells in vitro

1989 ◽  
Vol 92 (2) ◽  
pp. 231-239
Author(s):  
P.I. Francz ◽  
K. Bayreuther ◽  
H.P. Rodemann
Keyword(s):  
Protein Fraction ◽  
Fibroblast Cell ◽  
Cell Types ◽  
Specific Marker ◽  
Human Skin Fibroblast ◽  
Nuclear Fraction ◽  
Cell Type ◽  
Marker Proteins ◽  
Cell Type Specific ◽  
Membrane Bound

Methods for the selective enrichment of various subpopulations of the human skin fibroblast cell line HH-8 have been developed. These methods permit the selection of homogeneous populations of the three mitotic fibroblast cell types MF I, II and III, and the four postmitotic cell types PMF IV, V, VI and VII. These seven cell types exhibit differentiation-dependent and cell-type-specific patterns of [35S]methionine-labelled polypeptides in total soluble cytoplasmic and nuclear proteins, also in membrane-bound proteins, and in secreted proteins. In the differentiation sequence MF II-MF III-PMF IV - PMF V - PMF VI 14 cell-type-specific marker proteins have been found in the cytoplasmic and nuclear fraction, also 24 cell-type-specific marker proteins have been found in the membrane-bound protein fraction, and 11 cell-type-specific marker proteins in the secreted protein fraction. Markers in spontaneously arising and experimentally selected or induced populations of a single fibroblast cell type were found to be identical.

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