scholarly journals Manifold learning analysis suggests strategies to align single-cell multimodal data of neuronal electrophysiology and transcriptomics

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Jiawei Huang ◽  
Jie Sheng ◽  
Daifeng Wang
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Manifold Learning ◽  
Molecular Mechanisms ◽  
Single Cells ◽  
Cell Types ◽  
Functional Enrichment ◽  
Multimodal Data ◽  
Network Analyses ◽  
Manifold Alignment

AbstractRecent single-cell multimodal data reveal multi-scale characteristics of single cells, such as transcriptomics, morphology, and electrophysiology. However, integrating and analyzing such multimodal data to deeper understand functional genomics and gene regulation in various cellular characteristics remains elusive. To address this, we applied and benchmarked multiple machine learning methods to align gene expression and electrophysiological data of single neuronal cells in the mouse brain from the Brain Initiative. We found that nonlinear manifold learning outperforms other methods. After manifold alignment, the cells form clusters highly corresponding to transcriptomic and morphological cell types, suggesting a strong nonlinear relationship between gene expression and electrophysiology at the cell-type level. Also, the electrophysiological features are highly predictable by gene expression on the latent space from manifold alignment. The aligned cells further show continuous changes of electrophysiological features, implying cross-cluster gene expression transitions. Functional enrichment and gene regulatory network analyses for those cell clusters revealed potential genome functions and molecular mechanisms from gene expression to neuronal electrophysiology.

scholarly journals Manifold learning analysis reveals the functional genomics at the cell-type level for neuronal electrophysiology in the mouse brain

2020 ◽  
Author(s):  
Jiawei Huang ◽  
Daifeng Wang
Keyword(s):  
Gene Expression ◽  
Functional Genomics ◽  
Mouse Brain ◽  
Manifold Learning ◽  
Single Cells ◽  
Cell Types ◽  
Functional Enrichment ◽  
Cell Type ◽  
Network Analyses ◽  
Different Characteristics

AbstractRecent single-cell multi-modal data reveal different characteristics of single cells, such as transcriptomics, morphology, and electrophysiology. However, our understanding of functional genomics and gene regulation leading to the cellular characteristics remains elusive. To address this, we used emerging manifold learning to align gene expression and electrophysiological data of single neuronal cells in the mouse brain. After manifold alignment, the cell clusters highly correspond to transcriptomic and morphological cell-types, suggesting a strong nonlinear linkage between gene expression and electrophysiology at the cell-type level. Additional functional enrichment and gene regulatory network analyses revealed potential novel molecular mechanistic insights from genes to electrophysiology at cellular resolution.

MO262THE SINGLE-CELL TRANSCRIPTOMICS OF HUMAN IGA NEPHROPATHY

2021 ◽  
Vol 36 (Supplement_1) ◽  
Author(s):  
Yong Zhong ◽  
Xiangcheng Xiao
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Signaling Pathways ◽  
Iga Nephropathy ◽  
Molecular Mechanisms ◽  
Mesangial Cells ◽  
Therapeutic Targets ◽  
Cell Types ◽  
Receptor Crosstalk ◽  
Overt Proteinuria

Abstract Background and Aims The exact molecular mechanisms underlying IgA nephropathy (IgAN) remains incompletely defined. Therefore, it is necessary to further elucidate the mechanism of IgA nephropathy and find novel therapeutic targets. Method Single-cell RNA sequencing (scRNA-seq) was applied to kidney biopsies from 4 IgAN and 1 control subjects to define the transcriptomic landscape at the single-cell resolution. Unsupervised clustering analysis of kidney specimens was used to identify distinct cell clusters. Differentially expressed genes and potential signaling pathways involved in IgAN were also identified. Results Our analysis identified 14 cell subsets in kidney biopsies from IgAN patients, and analyzed changing gene expression in distinct renal cell types. We found increased mesangial expression of several novel genes including MALAT1, GADD45B, SOX4 and EDIL3, which were related to proliferation and matrix accumulation and have not been reported in IgAN previously. The overexpressed genes in tubule cells of IgAN were mainly enriched in inflammatory pathways including TNF signaling, IL-17 signaling and NOD-like receptor signaling. Moreover, the receptor-ligand crosstalk analysis revealed potential interactions between mesangial cells and other cells in IgAN. Specifically, IgAN with overt proteinuria displayed elevated genes participating in several signaling pathways which may be involved in pathogenesis of progression of IgAN. Conclusion The comprehensive analysis of kidney biopsy specimen demonstrated different gene expression profile, potential pathologic ligand-receptor crosstalk, signaling pathways in human IgAN. These results offer new insight into pathogenesis and identify new therapeutic targets for patients with IgA nephropathy.

scholarly journals Self-reporting transposons enable simultaneous readout of gene expression and transcription factor binding in single cells

2019 ◽  
Author(s):  
Arnav Moudgil ◽  
Michael N. Wilkinson ◽  
Xuhua Chen ◽  
June He ◽  
Alex J. Cammack ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcription Factor ◽  
Single Cell ◽  
Binding Sites ◽  
Expression Profiles ◽  
Single Cells ◽  
Gene Expression Profiles ◽  
Cell Types ◽  
Specific Cell

AbstractIn situ measurements of transcription factor (TF) binding are confounded by cellular heterogeneity and represent averaged profiles in complex tissues. Single cell RNA-seq (scRNA-seq) is capable of resolving different cell types based on gene expression profiles, but no technology exists to directly link specific cell types to the binding pattern of TFs in those cell types. Here, we present self-reporting transposons (SRTs) and their use in single cell calling cards (scCC), a novel assay for simultaneously capturing gene expression profiles and mapping TF binding sites in single cells. First, we show how the genomic locations of SRTs can be recovered from mRNA. Next, we demonstrate that SRTs deposited by the piggyBac transposase can be used to map the genome-wide localization of the TFs SP1, through a direct fusion of the two proteins, and BRD4, through its native affinity for piggyBac. We then present the scCC method, which maps SRTs from scRNA-seq libraries, thus enabling concomitant identification of cell types and TF binding sites in those same cells. As a proof-of-concept, we show recovery of cell type-specific BRD4 and SP1 binding sites from cultured cells. Finally, we map Brd4 binding sites in the mouse cortex at single cell resolution, thus establishing a new technique for studying TF biology in situ.

scholarly journals Single-Cell RNA Sequencing to Disentangle the Blood System

2021 ◽  
Vol 41 (3) ◽  
pp. 1012-1018
Author(s):  
Jean Acosta ◽  
Daniel Ssozi ◽  
Peter van Galen
Keyword(s):  
Blood Cell ◽  
Single Cell ◽  
Rna Sequencing ◽  
Molecular Mechanisms ◽  
Single Cells ◽  
Cell Types ◽  
Blood System ◽  
Differentiated Cells ◽  
Tissue Organization ◽  
Single Cell Rna Sequencing

The blood system is often represented as a tree-like structure with stem cells that give rise to mature blood cell types through a series of demarcated steps. Although this representation has served as a model of hierarchical tissue organization for decades, single-cell technologies are shedding new light on the abundance of cell type intermediates and the molecular mechanisms that ensure balanced replenishment of differentiated cells. In this Brief Review, we exemplify new insights into blood cell differentiation generated by single-cell RNA sequencing, summarize considerations for the application of this technology, and highlight innovations that are leading the way to understand hematopoiesis at the resolution of single cells. Graphic Abstract: A graphic abstract is available for this article.

scholarly journals RNA splicing programs define tissue compartments and cell types at single cell resolution

2021 ◽  
Author(s):  
Julia Eve Olivieri ◽  
Roozbeh Dehghannasiri ◽  
Peter Wang ◽  
SoRi Jang ◽  
Antoine de Morree ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
High Throughput ◽  
Rna Splicing ◽  
Single Cells ◽  
Cell Types ◽  
Mouse Lemur ◽  
Cell Type ◽  
Multiple Organs ◽  
Single Cell Pcr

More than 95% of human genes are alternatively spliced. Yet, the extent splicing is regulated at single-cell resolution has remained controversial due to both available data and methods to interpret it. We apply the SpliZ, a new statistical approach that is agnostic to transcript annotation, to detect cell-type-specific regulated splicing in > 110K carefully annotated single cells from 12 human tissues. Using 10x data for discovery, 9.1% of genes with computable SpliZ scores are cell-type specifically spliced. These results are validated with RNA FISH, single cell PCR, and in high throughput with Smart-seq2. Regulated splicing is found in ubiquitously expressed genes such as actin light chain subunit MYL6 and ribosomal protein RPS24, which has an epithelial-specific microexon. 13% of the statistically most variable splice sites in cell-type specifically regulated genes are also most variable in mouse lemur or mouse. SpliZ analysis further reveals 170 genes with regulated splicing during sperm development using, 10 of which are conserved in mouse and mouse lemur. The statistical properties of the SpliZ allow model-based identification of subpopulations within otherwise indistinguishable cells based on gene expression, illustrated by subpopulations of classical monocytes with stereotyped splicing, including an un-annotated exon, in SAT1, a Diamine acetyltransferase. Together, this unsupervised and annotation-free analysis of differential splicing in ultra high throughput droplet-based sequencing of human cells across multiple organs establishes splicing is regulated cell-type-specifically independent of gene expression.

scholarly journals Q&A: using Patch-seq to profile single cells

BMC Biology ◽  
2017 ◽  
Vol 15 (1) ◽  
Author(s):  
Cathryn R. Cadwell ◽  
Rickard Sandberg ◽  
Xiaolong Jiang ◽  
Andreas S. Tolias
Keyword(s):  
Gene Expression ◽  
Nervous System ◽  
Patch Clamp ◽  
Single Cell ◽  
Single Cells ◽  
Cell Types ◽  
Patch Clamp Recording ◽  
Electrophysiological Properties ◽  
Whole Cell Patch Clamp ◽  
Single Cell Rna Sequencing

Abstract Individual neurons vary widely in terms of their gene expression, morphology, and electrophysiological properties. While many techniques exist to study single-cell variability along one or two of these dimensions, very few techniques can assess all three features for a single cell. We recently developed Patch-seq, which combines whole-cell patch clamp recording with single-cell RNA-sequencing and immunohistochemistry to comprehensively profile the transcriptomic, morphologic, and physiologic features of individual neurons. Patch-seq can be broadly applied to characterize cell types in complex tissues such as the nervous system, and to study the transcriptional signatures underlying the multidimensional phenotypes of single cells.

scholarly journals Network Analyses Predict Small RNAs That Might Modulate Gene Expression in the Testis and Epididymis of Bos indicus Bulls

2021 ◽  
Vol 12 ◽  
Author(s):  
Andressa O. de Lima ◽  
Juliana Afonso ◽  
Janette Edson ◽  
Esteban Marcellin ◽  
Robin Palfreyman ◽  
...  
Keyword(s):  
Gene Expression ◽  
Small Rnas ◽  
Molecular Mechanisms ◽  
Bos Indicus ◽  
Male Gamete ◽  
Functional Enrichment ◽  
Pairwise Comparisons ◽  
Network Analyses ◽  
Germ Cell Differentiation ◽  
Network Cluster

Spermatogenesis relies on complex molecular mechanisms, essential for the genesis and differentiation of the male gamete. Germ cell differentiation starts at the testicular parenchyma and finishes in the epididymis, which has three main regions: head, body, and tail. RNA-sequencing data of the testicular parenchyma (TP), head epididymis (HE), and tail epididymis (TE) from four bulls (three biopsies per bull: 12 samples) were subjected to differential expression analyses, functional enrichment analyses, and co-expression analyses. The aim was to investigate the co-expression and infer possible regulatory roles for transcripts involved in the spermatogenesis of Bos indicus bulls. Across the three pairwise comparisons, 3,826 differentially expressed (DE) transcripts were identified, of which 384 are small RNAs. Functional enrichment analysis pointed to gene ontology (GO) terms related to ion channel activity, detoxification of copper, neuroactive receptors, and spermatogenesis. Using the regulatory impact factor (RIF) algorithm, we detected 70 DE small RNAs likely to regulate the DE transcripts considering all pairwise comparisons among tissues. The pattern of small RNA co-expression suggested that these elements are involved in spermatogenesis regulation. The 3,826 DE transcripts (mRNAs and small RNAs) were further subjected to co-expression analyses using the partial correlation and information theory (PCIT) algorithm for network prediction. Significant correlations underpinned the co-expression network, which had 2,216 transcripts connected by 158,807 predicted interactions. The larger network cluster was enriched for male gamete generation and had 15 miRNAs with significant RIF. The miRNA bta-mir-2886 showed the highest number of connections (601) and was predicted to down-regulate ELOVL3, FEZF2, and HOXA13 (negative co-expression correlations and confirmed with TargetScan). In short, we suggest that bta-mir-2886 and other small RNAs might modulate gene expression in the testis and epididymis, in Bos indicus cattle.

scholarly journals Identification of potential crucial genes and pathways associated with vein graft restenosis based on gene expression analysis in experimental rabbits

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e4704 ◽  
Author(s):  
Qiang Liu ◽  
Xiujie Yin ◽  
Mingzhu Li ◽  
Li Wan ◽  
Liqiao Liu ◽  
...  
Keyword(s):  
Gene Expression ◽  
High Throughput ◽  
Vein Graft ◽  
Molecular Mechanisms ◽  
Rapid Development ◽  
Bypass Graft ◽  
Functional Enrichment ◽  
Ppi Network ◽  
Hub Genes ◽  
Network Analyses

Occlusive artery disease (CAD) is the leading cause of death worldwide. Bypass graft surgery remains the most prevalently performed treatment for occlusive arterial disease, and veins are the most frequently used conduits for surgical revascularization. However, the clinical efficacy of bypass graft surgery is highly affected by the long-term potency rates of vein grafts, and no optimal treatments are available for the prevention of vein graft restenosis (VGR) at present. Hence, there is an urgent need to improve our understanding of the molecular mechanisms involved in mediating VGR. The past decade has seen the rapid development of genomic technologies, such as genome sequencing and microarray technologies, which will provide novel insights into potential molecular mechanisms involved in the VGR program. Ironically, high throughput data associated with VGR are extremely scarce. The main goal of the current study was to explore potential crucial genes and pathways associated with VGR and to provide valid biological information for further investigation of VGR. A comprehensive bioinformatics analysis was performed using high throughput gene expression data. Differentially expressed genes (DEGs) were identified using the R and Bioconductor packages. After functional enrichment analysis of the DEGs, protein–protein interaction (PPI) network and sub-PPI network analyses were performed. Finally, nine potential hub genes and fourteen pathways were identified. These hub genes may interact with each other and regulate the VGR program by modulating the cell cycle pathway. Future studies focusing on revealing the specific cellular and molecular mechanisms of these key genes and pathways involved in regulating the VGR program may provide novel therapeutic targets for VGR inhibition.

scholarly journals Single-Cell RNA Sequencing Reveals Multiple Pathways and the Tumor Microenvironment Could Lead to Chemotherapy Resistance in Cervical Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Meijia Gu ◽  
Ti He ◽  
Yuncong Yuan ◽  
Suling Duan ◽  
Xin Li ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cervical Cancer ◽  
Tumor Microenvironment ◽  
Single Cell ◽  
Rna Sequencing ◽  
Cancer Biology ◽  
Chemotherapy Resistance ◽  
Cell Types ◽  
Functional Enrichment ◽  
Single Cell Rna Sequencing

BackgroundCervical cancer is one of the most common gynecological cancers worldwide. The tumor microenvironment significantly influences the therapeutic response and clinical outcome. However, the complex tumor microenvironment of cervical cancer and the molecular mechanisms underlying chemotherapy resistance are not well studied. This study aimed to comprehensively analyze cells from pretreated and chemoresistant cervical cancer tissues to generate a molecular census of cell populations.MethodsBiopsy tissues collected from patients with cervical squamous cell carcinoma, cervical adenocarcinoma, and chronic cervicitis were subjected to single-cell RNA sequencing using the 10× Genomics platform. Unsupervised clustering analysis of cells was performed to identify the main cell types, and important cell clusters were reclustered into subpopulations. Gene expression profiles and functional enrichment analysis were used to explore gene expression and functional differences between cell subpopulations in cervicitis and cervical cancer samples and between chemoresistant and chemosensitive samples.ResultsA total of 24,371 cells were clustered into nine separate cell types, including immune and non-immune cells. Differentially expressed genes between chemoresistant and chemosensitive patients enriched in the phosphoinositide 3-kinase (PI3K)/AKT pathway were involved in tumor development, progression, and apoptosis, which might lead to chemotherapy resistance.ConclusionsOur study provides a comprehensive overview of the cancer microenvironment landscape and characterizes its gene expression and functional difference in chemotherapy resistance. Consequently, our study deepens the insights into cervical cancer biology through the identification of gene markers for diagnosis, prognosis, and therapy.

scholarly journals Single-cell regulatory landscape and disease vulnerability map of adult Macaque cortex

2020 ◽  
Author(s):  
Ying Lei ◽  
Mengnan Cheng ◽  
Zihao Li ◽  
Zhenkun Zhuang ◽  
Liang Wu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Primary Motor Cortex ◽  
Neurological Diseases ◽  
Single Cells ◽  
Cell Types ◽  
Regulatory Elements ◽  
Chromatin Accessibility ◽  
Nucleotide Polymorphisms ◽  
Cell Type

Non-human primates (NHP) provide a unique opportunity to study human neurological diseases, yet detailed characterization of the cell types and transcriptional regulatory features in the NHP brain is lacking. We applied a combinatorial indexing assay, sci-ATAC-seq, as well as single-nuclei RNA-seq, to profile chromatin accessibility in 43,793 single cells and transcriptomics in 11,477 cells, respectively, from prefrontal cortex, primary motor cortex and the primary visual cortex of adult cynomolgus monkey Macaca fascularis. Integrative analysis of these two datasets, resolved regulatory elements and transcription factors that specify cell type distinctions, and discovered area-specific diversity in chromatin accessibility and gene expression within excitatory neurons. We also constructed the dynamic landscape of chromatin accessibility and gene expression of oligodendrocyte maturation to characterize adult remyelination. Furthermore, we identified cell type-specific enrichment of differentially spliced gene isoforms and disease-associated single nucleotide polymorphisms. Our datasets permit integrative exploration of complex regulatory dynamics in macaque brain tissue at single-cell resolution.

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