scholarly journals Detection of allele-specific expression in spatial transcriptomics with spASE

2021 ◽  
Author(s):  
Luli S. Zou ◽  
Tongtong Zhao ◽  
Dylan M. Cable ◽  
Evan Murray ◽  
Martin J. Aryee ◽  
...  
Keyword(s):  
Statistical Power ◽  
Cell Types ◽  
Cell Type ◽  
Specific Expression ◽  
Allele Specific Expression ◽  
Preferential Expression ◽  
Mouse Hippocampus ◽  
Transcriptomics Data ◽  
Allele Specific ◽  
Cell Type Specific

AbstractAllele-specific expression (ASE), or the preferential expression of one allele, can be observed in transcriptomics data from early development throughout the lifespan. However, the prevalence of spatial and cell type-specific ASE variation remains unclear. Spatial transcriptomics technologies permit the study of spatial ASE patterns genome-wide at near-single-cell resolution. However, the data are highly sparse, and confounding between cell type and spatial location present further statistical challenges. Here, we introduce spASE (https://github.com/lulizou/spase), a computational framework for detecting spatial patterns in ASE within and across cell types from spatial transcriptomics data. To tackle the challenge presented by the low signal to noise ratio due to the sparsity of the data, we implement a spatial smoothing approach that greatly improves statistical power. We generated Slide-seqV2 data from the mouse hippocampus and detected ASE in X-chromosome genes, both within and across cell type, validating our ability to recover known ASE patterns. We demonstrate that our method can also identify cell type-specific effects, which we find can explain the majority of the spatial signal for autosomal genes. The findings facilitated by our method provide new insight into the uncharacterized landscape of spatial and cell type-specific ASE in the mouse hippocampus.

scholarly journals Genetic influences on cell type specific gene expression and splicing during neurogenesis elucidate regulatory mechanisms of brain traits

2020 ◽  
Author(s):  
Nil Aygün ◽  
Angela L. Elwell ◽  
Dan Liang ◽  
Michael J. Lafferty ◽  
Kerry E. Cheek ◽  
...  
Keyword(s):  
Gene Expression ◽  
Regulatory Elements ◽  
Regulatory Mechanisms ◽  
Specific Gene ◽  
Cell Type ◽  
Specific Expression ◽  
Risk Variants ◽  
Allele Specific ◽  
Cell Type Specific ◽  
Regulatory Effects

SummaryInterpretation of the function of non-coding risk loci for neuropsychiatric disorders and brain-relevant traits via gene expression and alternative splicing is mainly performed in bulk post-mortem adult tissue. However, genetic risk loci are enriched in regulatory elements of cells present during neocortical differentiation, and regulatory effects of risk variants may be masked by heterogeneity in bulk tissue. Here, we map e/sQTLs and allele specific expression in primary human neural progenitors (n=85) and their sorted neuronal progeny (n=74). Using colocalization and TWAS, we uncover cell-type specific regulatory mechanisms underlying risk for these traits.

scholarly journals Cell-type Specific Expression Quantitative Trait Loci Associated with Alzheimer Disease in Blood and Brain Tissue

2020 ◽  
Author(s):  
Devanshi Patel ◽  
Xiaoling Zhang ◽  
John J. Farrell ◽  
Jaeyoon Chung ◽  
Thor D. Stein ◽  
...  
Keyword(s):  
Gene Expression ◽  
Quantitative Trait ◽  
Expression Patterns ◽  
Regulation Of Gene Expression ◽  
Cell Types ◽  
Eqtl Analysis ◽  
Cell Type ◽  
Specific Expression ◽  
Cell Type Specific Expression ◽  
Cell Type Specific

ABSTRACTBecause regulation of gene expression is heritable and context-dependent, we investigated AD-related gene expression patterns in cell-types in blood and brain. Cis-expression quantitative trait locus (eQTL) mapping was performed genome-wide in blood from 5,257 Framingham Heart Study (FHS) participants and in brain donated by 475 Religious Orders Study/Memory & Aging Project (ROSMAP) participants. The association of gene expression with genotypes for all cis SNPs within 1Mb of genes was evaluated using linear regression models for unrelated subjects and linear mixed models for related subjects. Cell type-specific eQTL (ct-eQTL) models included an interaction term for expression of “proxy” genes that discriminate particular cell type. Ct-eQTL analysis identified 11,649 and 2,533 additional significant gene-SNP eQTL pairs in brain and blood, respectively, that were not detected in generic eQTL analysis. Of note, 386 unique target eGenes of significant eQTLs shared between blood and brain were enriched in apoptosis and Wnt signaling pathways. Five of these shared genes are established AD loci. The potential importance and relevance to AD of significant results in myeloid cell-types is supported by the observation that a large portion of GWS ct-eQTLs map within 1Mb of established AD loci and 58% (23/40) of the most significant eGenes in these eQTLs have previously been implicated in AD. This study identified cell-type specific expression patterns for established and potentially novel AD genes, found additional evidence for the role of myeloid cells in AD risk, and discovered potential novel blood and brain AD biomarkers that highlight the importance of cell-type specific analysis.

scholarly journals Cell type-specific expression of Eps8 in the mouse hippocampus

2014 ◽  
Vol 15 (1) ◽  
pp. 26 ◽  
Author(s):  
Chiung-Chun Huang ◽  
Yun-Shen Lin ◽  
Cheng-Che Lee ◽  
Kuei-Sen Hsu
Keyword(s):  
Cell Type ◽  
Specific Expression ◽  
Mouse Hippocampus ◽  
Cell Type Specific Expression ◽  
Cell Type Specific

scholarly journals A Statistical Framework to Identify Cell Types Whose Genetically Regulated Proportions are Associated with Complex Diseases

2021 ◽  
Author(s):  
Hongyu Zhao ◽  
Wei Liu ◽  
Wenxuan Deng ◽  
Ming Chen ◽  
Zihan Dong ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Statistical Power ◽  
Predictive Biomarkers ◽  
Complex Diseases ◽  
Cell Types ◽  
Chronic Obstructive ◽  
Cell Type ◽  
Obstructive Pulmonary Disease ◽  
Statistical Framework ◽  
Transcriptomics Data

Abstract Finding disease-relevant tissues and cell types can facilitate the identification and investigation of functional genes and variants. In particular, cell type proportions can serve as potential disease predictive biomarkers. Here, we introduce a novel statistical framework, cell-type Wide Association Study (cWAS), that integrates genetic data with transcriptomics data to identify cell types whose genetically regulated proportions (GRPs) are disease/trait-associated. On simulated and real GWAS data, cWAS showed substantial statistical power with newly identified significant GRP associations in disease-associated tissues. More specifically, GRPs of endothelial and myofibroblast in the lung tissue were associated with Idiopathic Pulmonary Fibrosis and Chronic Obstructive Pulmonary Disease, respectively. For breast cancer, the GRP of blood CD8+ T cells was negatively associated with breast cancer (BC) risk as well as survival. Overall, cWAS is a powerful tool to reveal cell types associated with complex diseases mediated by GRPs.

scholarly journals Single-cell RNA-sequencing reveals thoracolumbar vertebra heterogeneity and rib-genesis in pigs

2021 ◽  
Author(s):  
Jianbo Li ◽  
Ligang Wang ◽  
Dawei Yu ◽  
Junfeng Hao ◽  
Longchao Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Lumbar Vertebra ◽  
Cell Types ◽  
Cell Type ◽  
Specific Expression ◽  
Coupled Process ◽  
Gene Expression Dynamics ◽  
Cell Type Specific ◽  
Thoracolumbar Vertebra

Thoracolumbar vertebra (TLV) and rib primordium (RP) development is a common evolutionary feature across vertebrates although whole-organism analysis of TLV and RP gene expression dynamics has been lacking. Here we investigated the single-cell transcriptomic landscape of thoracic vertebra (TV), lumbar vertebra (LV), and RP cells from a pig embryo at 27 days post-fertilization (dpf) and identified six cell types with distinct gene-expression signatures. In-depth dissection of the gene-expression dynamics and RNA velocity revealed a coupled process of osteogenesis and angiogenesis during TLV and rib development. Further analysis of cell-type-specific and strand-specific expression uncovered the extremely high levels of HOXA10 3'-UTR sequence specific to osteoblast of LV cells, which may function as anti-HOXA10-antisense by counteracting the HOXA10-antisense effect to determine TLV transition. Thus, this work provides a valuable resource for understanding embryonic osteogenesis and angiogenesis underlying vertebrate TLV and RP development at the cell-type-specific resolution, which serves as a comprehensive view on the transcriptional profile of animal embryo development.

scholarly journals Dynamics of gene expression in single root cells ofA. thaliana

2018 ◽  
Author(s):  
Ken Jean-Baptiste ◽  
José L. McFaline-Figueroa ◽  
Cristina M. Alexandre ◽  
Michael W. Dorrity ◽  
Lauren Saunders ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Developmental Trajectories ◽  
Cell Types ◽  
Cell Type ◽  
Specific Expression ◽  
Root Cells ◽  
Cell Lineages ◽  
Cell Type Specific Expression ◽  
Cell Type Specific

ABSTRACTSingle-cell RNA-seq can yield high-resolution cell-type-specific expression signatures that reveal new cell types and the developmental trajectories of cell lineages. Here, we apply this approach toA. thalianaroot cells to capture gene expression in 3,121 root cells. We analyze these data with Monocle 3, which orders single cell transcriptomes in an unsupervised manner and uses machine learning to reconstruct single-cell developmental trajectories along pseudotime. We identify hundreds of genes with cell-type-specific expression, with pseudotime analysis of several cell lineages revealing both known and novel genes that are expressed along a developmental trajectory. We identify transcription factor motifs that are enriched in early and late cells, together with the corresponding candidate transcription factors that likely drive the observed expression patterns. We assess and interpret changes in total RNA expression along developmental trajectories and show that trajectory branch points mark developmental decisions. Finally, by applying heat stress to whole seedlings, we address the longstanding question of possible heterogeneity among cell types in the response to an abiotic stress. Although the response of canonical heat shock genes dominates expression across cell types, subtle but significant differences in other genes can be detected among cell types. Taken together, our results demonstrate that single-cell transcriptomics holds promise for studying plant development and plant physiology with unprecedented resolution.

scholarly journals Cell type-specific biotin labeling in vivo resolves regional neuronal proteomic differences in mouse brain

2021 ◽  
Author(s):  
Sruti Rayaprolu ◽  
Sara Bitarafan ◽  
Ranjita Betarbet ◽  
Sydney N Sunna ◽  
Lihong Cheng ◽  
...  
Keyword(s):  
Mouse Brain ◽  
Neurological Diseases ◽  
Neuronal Cell ◽  
Cell Types ◽  
Proteomic Profiling ◽  
Cell Type ◽  
Specific Expression ◽  
Cell Type Specific ◽  
The Brain

Isolation and proteomic profiling of brain cell types, particularly neurons, pose several technical challenges which limit our ability to resolve distinct cellular phenotypes in neurological diseases. Therefore, we generated a novel mouse line that enables cell type-specific expression of a biotin ligase, TurboID, via Cre-lox strategy for in vivo proximity-dependent biotinylation of proteins. Using adenoviral-based and transgenic approaches, we show striking protein biotinylation in neuronal cell bodies and axons throughout the mouse brain. We quantified more than 2,000 neuron-derived proteins following enrichment that mapped to numerous subcellular compartments. Synaptic, transmembrane transporters, ion channel subunits, and disease-relevant druggable targets were among the most significantly enriched proteins. Remarkably, we resolved brain region-specific proteomic profiles of Camk2a neurons with distinct functional molecular signatures and disease associations that may underlie regional neuronal vulnerability. Leveraging the neuronal specificity of this in vivo biotinylation strategy, we used an antibody-based approach to uncover regionally unique patterns of neuron-derived signaling phospho-proteins and cytokines, particularly in the cortex and cerebellum. Our work provides a proteomic framework to investigate cell type-specific mechanisms driving physiological and pathological states of the brain as well as complex tissues beyond the brain.

scholarly journals Cell-Type Specific Analysis of Selenium-Related Genes in Brain

Antioxidants ◽  
2019 ◽  
Vol 8 (5) ◽  
pp. 120
Author(s):  
Alexandru R. Sasuclark ◽  
Vedbar S. Khadka ◽  
Matthew W. Pitts
Keyword(s):  
Neural Development ◽  
Cortical Neurons ◽  
Cell Types ◽  
Inhibitory Neurons ◽  
Brain Atlas ◽  
Cell Type ◽  
Specific Expression ◽  
Rnaseq Data ◽  
Cell Type Specific Expression ◽  
Cell Type Specific

Selenoproteins are a unique class of proteins that play key roles in redox signaling in the brain. This unique organ is comprised of a wide variety of cell types that includes excitatory neurons, inhibitory neurons, astrocytes, microglia, and oligodendrocytes. Whereas selenoproteins are known to be required for neural development and function, the cell-type specific expression of selenoproteins and selenium-related machinery has yet to be systematically investigated. Due to advances in sequencing technology and investment from the National Institutes of Health (NIH)-sponsored BRAIN initiative, RNA sequencing (RNAseq) data from thousands of cortical neurons can now be freely accessed and searched using the online RNAseq data navigator at the Allen Brain Atlas. Hence, we utilized this newly developed tool to perform a comprehensive analysis of the cell-type specific expression of selenium-related genes in brain. Select proteins of interest were further verified by means of multi-label immunofluorescent labeling of mouse brain sections. Of potential significance to neural selenium homeostasis, we report co-expression of selenoprotein P (SELENOP) and selenium binding protein 1 (SELENBP1) within astrocytes. These findings raise the intriguing possibility that SELENBP1 may negatively regulate astrocytic SELENOP synthesis and thereby limit downstream Se supply to neurons.

scholarly journals A novel method to identify cell-type specific regulatory variants and their role in cancer risk

2021 ◽  
Author(s):  
Cynthia A Kalita ◽  
Alexander Gusev
Keyword(s):  
Cancer Risk ◽  
Cell Types ◽  
New Method ◽  
Rna Seq ◽  
Cell Type ◽  
Regulatory Variants ◽  
Specific Effects ◽  
Allele Specific ◽  
Cell Type Specific ◽  
Eqtl Data

Background: Expression quantitative trait loci (eQTLs) have been crucial in providing an understanding of how genetic variants influence gene expression. However, eQTLs are known to exert cell type specific effects, and existing methods to identify cell type specific QTLs in bulk data require large sample sizes. Results: Here, we propose DeCAF (DEconvoluted cell type Allele specific Function), a new method to identify cell-fraction (cf) QTLs in tumors by leveraging both allelic and total expression information. Applying DeCAF to RNA-seq data from TCGA, we identified 3,664 genes with cfQTLs (at 10% FDR) in 14 cell types, a 5.63x increase in discovery over conventional interaction-eQTL mapping. cfQTLs replicated in external cell type specific eQTL data and were more enriched for cancer risk than conventional eQTLs. The intersection of tumor-specific QTL effects (tsQTLs) with GWAS loci identified rs4765621 and SCARB1, which has been previously linked to renal cell carcinoma (RCC) progression and experimentally validated in tumors. Conclusions: Our new method, DeCAF, empowers the discovery of biologically meaningful cfQTLs from bulk RNA-seq data in moderately sized studies. Our study contributes to a better understanding of germline mechanisms underlying the anticancer immune response as well as cfQTLs contributing to cancer risk.

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