scholarly journals Gene Module Analysis Reveals Cell-Type Specificity and Potential Target Genes in Autism’s Pathogenesis

Biomedicines ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 410
Author(s):  
Guoli Ji ◽  
Shuchao Li ◽  
Lishan Ye ◽  
Jinting Guan
Keyword(s):  
Target Genes ◽  
Neurodevelopmental Disorder ◽  
Expression Patterns ◽  
Autism Spectrum ◽  
Anterior Cingulate ◽  
Specific Gene ◽  
Cell Type ◽  
Sequencing Data ◽  
Cell Type Specific ◽  
Gene Modules

Multiple genetic factors contribute to the pathogenesis of autism spectrum disorder (ASD), a kind of neurodevelopmental disorder. Genes were usually studied separately for their associations with ASD. However, genes associated with ASD do not act alone but interact with each other in a network module. The identification of these modules is the basis for the systematic understanding of the pathogenesis of ASD. Moreover, ASD is characterized by highly pathogenic heterogeneity, and gene modules associated with ASD are cell-type-specific. In this study, based on the single-nucleus RNA sequencing data of 41 post-mortem tissue samples from the prefrontal cortex and anterior cingulate cortex of 19 ASD patients and 16 control individuals, we applied sparse module activity factorization, a matrix decomposition method consistent with the multi-factor and heterogeneous characteristics of ASD pathogenesis, to identify cell-type-specific gene modules. Then, statistical procedures were performed to detect highly reproducible cell-type-specific ASD-associated gene modules. Through the enrichment analysis of cell markers, 31 cell-type-specific gene modules related to ASD were further screened out. These 31 gene modules are all enriched with curated ASD risk genes. Finally, we utilized the expression patterns of these cell-type-specific ASD-associated gene modules to build predictive models for ASD. The excellent predictive performance also proved the associations between these gene modules and ASD. Our study confirmed the multifactorial and cell-type-specific characteristics of ASD pathogeneses. The results showed that excitatory neurons such as L2/3, L4, and L5/6-CC play essential roles in ASD’s pathogenic processes. We identified the potential ASD target genes that act together in cell-type-specific modules, such as NRG3, KCNIP4, BAI3, PTPRD, LRRTM4, and LINGO2 in the L2/3 gene modules. Our study offers new potential genomic targets for ASD and provides a novel method to study gene modules involved in the pathogenesis of ASD.

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.

scholarly journals CT-FOCS: a novel method for inferring cell type-specific enhancer-promoter maps

2019 ◽  
Author(s):  
Tom Aharon Hait ◽  
Ran Elkon ◽  
Ron Shamir
Keyword(s):  
Gene Expression ◽  
Target Genes ◽  
Expression Patterns ◽  
Cell Types ◽  
Specific Gene ◽  
Cell Type ◽  
Chromatin Interactions ◽  
Cell Type Specific ◽  
Novel Method ◽  
Validation Scheme

AbstractSpatiotemporal gene expression patterns are governed to a large extent by enhancer elements, typically located distally from their target genes. Identification of enhancer-promoter (EP) links that are specific and functional in individual cell types is a key challenge in understanding gene regulation. We introduce CT-FOCS, a new statistical inference method that utilizes multiple replicates per cell type to infer cell type-specific EP links. Computationally predicted EP links are usually benchmarked against experimentally determined chromatin interactions measured by ChIA-PET and promoter-capture HiC techniques. We expand this validation scheme by using also loops that overlap in their anchor sites. In analyzing 1,366 samples from ENCODE, Roadmap epigenomics and FANTOM5, CT-FOCS inferred highly cell type-specific EP links more accurately than state-of-the-art methods. We illustrate how our inferred EP links drive cell type-specific gene expression and regulation.

scholarly journals Comprehensive analysis of single cell ATAC-seq data with SnapATAC

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Rongxin Fang ◽  
Sebastian Preissl ◽  
Yang Li ◽  
Xiaomeng Hou ◽  
Jacinta Lucero ◽  
...  
Keyword(s):  
Single Cell ◽  
Single Cell Analysis ◽  
Expression Patterns ◽  
Regulatory Elements ◽  
Cellular Heterogeneity ◽  
Specific Gene ◽  
Open Chromatin ◽  
Cell Type ◽  
Process Data ◽  
Cell Type Specific

AbstractIdentification of the cis-regulatory elements controlling cell-type specific gene expression patterns is essential for understanding the origin of cellular diversity. Conventional assays to map regulatory elements via open chromatin analysis of primary tissues is hindered by sample heterogeneity. Single cell analysis of accessible chromatin (scATAC-seq) can overcome this limitation. However, the high-level noise of each single cell profile and the large volume of data pose unique computational challenges. Here, we introduce SnapATAC, a software package for analyzing scATAC-seq datasets. SnapATAC dissects cellular heterogeneity in an unbiased manner and map the trajectories of cellular states. Using the Nyström method, SnapATAC can process data from up to a million cells. Furthermore, SnapATAC incorporates existing tools into a comprehensive package for analyzing single cell ATAC-seq dataset. As demonstration of its utility, SnapATAC is applied to 55,592 single-nucleus ATAC-seq profiles from the mouse secondary motor cortex. The analysis reveals ~370,000 candidate regulatory elements in 31 distinct cell populations in this brain region and inferred candidate cell-type specific transcriptional regulators.

New insights into promoter–enhancer communication mechanisms revealed by dynamic single-molecule imaging

2021 ◽  
Author(s):  
Jieru Li ◽  
Alexandros Pertsinidis
Keyword(s):  
Gene Expression ◽  
Single Molecule ◽  
Target Genes ◽  
Regulatory Elements ◽  
Specific Gene ◽  
Single Molecule Imaging ◽  
Cell Type ◽  
Regulatory Information ◽  
Cell Type Specific ◽  
Target Promoters

Establishing cell-type-specific gene expression programs relies on the action of distal enhancers, cis-regulatory elements that can activate target genes over large genomic distances — up to Mega-bases away. How distal enhancers physically relay regulatory information to target promoters has remained a mystery. Here, we review the latest developments and insights into promoter–enhancer communication mechanisms revealed by live-cell, real-time single-molecule imaging approaches.

scholarly journals Microgenomic analysis reveals cell type-specific gene expression patterns between ray and fusiform initials within the cambial meristem ofPopulus

2008 ◽  
Vol 180 (1) ◽  
pp. 45-56 ◽  
Author(s):  
Nadia Goué ◽  
Marie-Claude Lesage-Descauses ◽  
Ewa J. Mellerowicz ◽  
Elisabeth Magel ◽  
Philippe Label ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Patterns ◽  
Gene Expression Patterns ◽  
Specific Gene ◽  
Cell Type ◽  
Specific Gene Expression ◽  
Fusiform Initials ◽  
Cell Type Specific

scholarly journals Genetic, parental and lifestyle factors influence telomere length

2021 ◽  
Author(s):  
Sergio Andreu-Sanchez ◽  
Geraldine Aubert ◽  
Aida Ripoll-Cladellas ◽  
Sandra Henkelman ◽  
Daria V. Zhernakova ◽  
...  
Keyword(s):  
Gene Expression ◽  
Average Length ◽  
Cell Types ◽  
Paternal Age ◽  
Specific Gene ◽  
Cell Type ◽  
Sequencing Data ◽  
Nonsense Mediated Decay ◽  
Cell Type Specific ◽  
Telomere Biology

The average length of telomere repeats (TL) declines with age and is considered to be a marker of biological ageing. Here, we measured TL in six blood cell types from 1,046 individuals using the clinically validated Flow-FISH method. We identified remarkable cell-type-specific variations in TL. Host genetics, environmental, parental and intrinsic factors such as sex, parental age, and smoking are associated to variations in TL. By analysing the genome-wide methylation patterns, we identified that the association of maternal, but not paternal, age to TL is mediated by epigenetics. Coupling these measurements to single-cell RNA-sequencing data for 62 participants revealed differential gene expression in T-cells. Genes negatively associated with TL were enriched for pathways related to translation and nonsense-mediated decay. Altogether, this study addresses cell-type-specific differences in telomere biology and its relation to cell-type-specific gene expression and highlights how perinatal factors play a role in determining TL, on top of genetics and lifestyle.

Single-cell RNA-seq reveals the transcriptional landscape in ischemic stroke

2021 ◽  
pp. 0271678X2110267
Author(s):  
Kai Zheng ◽  
Lingmin Lin ◽  
Wei Jiang ◽  
Lin Chen ◽  
Xiyue Zhang ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Single Cell ◽  
Expression Patterns ◽  
Cellular Heterogeneity ◽  
Ependymal Cells ◽  
Specific Gene ◽  
Specific Cell ◽  
Cell Type ◽  
Cns Inflammation ◽  
Cell Type Specific

Ischemic stroke (IS) is a detrimental neurological disease with limited treatments options. It has been challenging to define the roles of brain cell subsets in IS onset and progression due to cellular heterogeneity in the CNS. Here, we employed single-cell RNA sequencing (scRNA-seq) to comprehensively map the cell populations in the mouse model of MCAO (middle cerebral artery occlusion). We identified 17 principal brain clusters with cell-type specific gene expression patterns as well as specific cell subpopulations and their functions in various pathways. The CNS inflammation triggered upregulation of key cell type-specific genes unpublished before. Notably, microglia displayed a cell differentiation diversity after stroke among its five distinct subtypes. Importantly, we found the potential trajectory branches of the monocytes/macrophage’s subsets. Finally, we also identified distinct subclusters among brain vasculature cells, ependymal cells and other glia cells. Overall, scRNA-seq revealed the precise transcriptional changes during neuroinflammation at the single-cell level, opening up a new field for exploration of the disease mechanisms and drug discovery in stroke based on the cell-subtype specific molecules.

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