scholarly journals Spatially resolved transcriptomics in immersive environments

2022 ◽  
Vol 5 (1) ◽  
Author(s):  
Denis Bienroth ◽  
Hieu T. Nim ◽  
Dimitar Garkov ◽  
Karsten Klein ◽  
Sabrina Jaeger-Honz ◽  
...  
Keyword(s):  
Virtual Reality ◽  
Spatial Information ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Immersive Environments ◽  
Visualization System ◽  
Head Mounted Display ◽  
Spatially Resolved ◽  
Expression Of Genes ◽  
Fish Tank

AbstractSpatially resolved transcriptomics is an emerging class of high-throughput technologies that enable biologists to systematically investigate the expression of genes along with spatial information. Upon data acquisition, one major hurdle is the subsequent interpretation and visualization of the datasets acquired. To address this challenge, VR-Cardiomicsis presented, which is a novel data visualization system with interactive functionalities designed to help biologists interpret spatially resolved transcriptomic datasets. By implementing the system in two separate immersive environments, fish tank virtual reality (FTVR) and head-mounted display virtual reality (HMD-VR), biologists can interact with the data in novel ways not previously possible, such as visually exploring the gene expression patterns of an organ, and comparing genes based on their 3D expression profiles. Further, a biologist-driven use-case is presented, in which immersive environments facilitate biologists to explore and compare the heart expression profiles of different genes.

scholarly journals Deciphering spatial domains from spatially resolved transcriptomics with adaptive graph attention auto-encoder

2021 ◽  
Author(s):  
Kangning Dong ◽  
Shihua Zhang
Keyword(s):  
Gene Expression ◽  
Spatial Information ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Identification Accuracy ◽  
Spatial Context ◽  
Gene Expressions ◽  
Spatially Resolved ◽  
Spatial Domains

Recent advances in spatially resolved transcriptomics have enabled comprehensive measurements of gene expression patterns while retaining spatial context of tissue microenvironment. Deciphering the spatial context of spots in a tissue needs to use their spatial information carefully. To this end, we developed a graph attention auto- encoder framework STGATE to accurately identify spatial domains by learning low-dimensional latent embeddings via integrating spatial information and gene expression profiles. To better characterize the spatial similarity at the boundary of spatial domains, STGATE adopts an attention mechanism to adaptively learn the similarity of neighboring spots, and an optional cell type-aware module through integrating the pre-clustering of gene expressions. We validated STGATE on diverse spatial transcriptomics datasets generated by different platforms with different spatial resolutions. STGATE could substantially improve the identification accuracy of spatial domains, and denoise the data while preserving spatial expression patterns. Importantly, STGATE could be extended to multiple consecutive sections for reducing batch effects between sections and extracting 3D expression domains from the reconstructed 3D tissue effectively.

Immersive Visualization of Virtual 3D City Models and its Applications in E-Planning

2012 ◽  
Vol 1 (4) ◽  
pp. 17-34 ◽  
Author(s):  
Juri Engel ◽  
Jürgen Döllner
Keyword(s):  
Large Scale ◽  
Spatial Information ◽  
Immersive Environments ◽  
Camera System ◽  
Visualization System ◽  
3D City Models ◽  
3D Rendering ◽  
Planning Models ◽  
Immersive Visualization ◽  
City Models

Immersive visualization offers an intuitive access to and an effective way of realizing, exploring, and analyzing virtual 3D city models, which are essential tools for effective communication and management of complex urban spatial information in e-planning. In particular, immersive visualization allows for simulating planning scenarios and to receive a close-to-reality impression by both non-expert and expert stakeholders. This contribution is concerned with the main requirements and technical concepts of a system for visualizing virtual 3D city models in large-scale, fully immersive environments. It allows stakeholders ranging from citizens to decision-makers to explore and examine the virtual 3D city model and embedded planning models “in situ.” Fully immersive environments involve a number of specific requirements for both hardware and 3D rendering including enhanced 3D rendering techniques, an immersion-aware, autonomous, and assistive 3D camera system, and a synthetic, immersion-supporting soundscape. Based on these requirements, the authors have implemented a prototypical visualization system that the authors present in this article. The characteristics of fully immersive visualization enable a number of new applications within e-planning workflows and processes, in particular, with respect to public participation, decision support, and location marketing.

scholarly journals Spatial transcriptome profiling by MERFISH reveals subcellular RNA compartmentalization and cell cycle-dependent gene expression

2019 ◽  
Vol 116 (39) ◽  
pp. 19490-19499 ◽  
Author(s):  
Chenglong Xia ◽  
Jean Fan ◽  
George Emanuel ◽  
Junjie Hao ◽  
Xiaowei Zhuang
Keyword(s):  
Gene Expression ◽  
Cell Cycle ◽  
Spatial Information ◽  
Detection Efficiency ◽  
Expression Profiles ◽  
Regulation Of Gene Expression ◽  
Rna Profiling ◽  
Spatially Resolved ◽  
Cycle Dependent

The expression profiles and spatial distributions of RNAs regulate many cellular functions. Image-based transcriptomic approaches provide powerful means to measure both expression and spatial information of RNAs in individual cells within their native environment. Among these approaches, multiplexed error-robust fluorescence in situ hybridization (MERFISH) has achieved spatially resolved RNA quantification at transcriptome scale by massively multiplexing single-molecule FISH measurements. Here, we increased the gene throughput of MERFISH and demonstrated simultaneous measurements of RNA transcripts from ∼10,000 genes in individual cells with ∼80% detection efficiency and ∼4% misidentification rate. We combined MERFISH with cellular structure imaging to determine subcellular compartmentalization of RNAs. We validated this approach by showing enrichment of secretome transcripts at the endoplasmic reticulum, and further revealed enrichment of long noncoding RNAs, RNAs with retained introns, and a subgroup of protein-coding mRNAs in the cell nucleus. Leveraging spatially resolved RNA profiling, we developed an approach to determine RNA velocity in situ using the balance of nuclear versus cytoplasmic RNA counts. We applied this approach to infer pseudotime ordering of cells and identified cells at different cell-cycle states, revealing ∼1,600 genes with putative cell cycle-dependent expression and a gradual transcription profile change as cells progress through cell-cycle stages. Our analysis further revealed cell cycle-dependent and cell cycle-independent spatial heterogeneity of transcriptionally distinct cells. We envision that the ability to perform spatially resolved, genome-wide RNA profiling with high detection efficiency and accuracy by MERFISH could help address a wide array of questions ranging from the regulation of gene expression in cells to the development of cell fate and organization in tissues.

scholarly journals The Expression of Human Placental Genes Related to Carotenoid/retinoid Metabolism and Pathways (P02-005-19)

2019 ◽  
Vol 3 (Supplement_1) ◽  
Author(s):  
Xiaoming Gong ◽  
Lewis Rubin
Keyword(s):  
Gene Expression ◽  
Microarray Analysis ◽  
Fetal Development ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Set Enrichment Analysis ◽  
Differentially Expressed ◽  
Retinoid Metabolism ◽  
Expression Of Genes ◽  
Β Carotene

Abstract Objectives Carotenoid/retinoids status and metabolism are essential for normal placental and fetal development. Both deficiencies and excess of retinoids and some carotenoids are associated with adverse pregnancy outcomes, such as preeclampsia and preterm birth. A group of important genes involved in regulating carotenoid/retinoid metabolism and maternal to fetal transfer in human placenta. The objective of this study is to analyze (a) the expression of genes critical for regulating carotenoid/retinoid metabolism and maternal-fetal transport in human trophoblasts and (b) placental transcriptional profiles of these pathways in response to carotenoid exposure. Methods Human cytotrophoblasts (CTBs) were isolated from term placentas. CTB RNA was used to analyze the expression of genes involved in carotenoid/retinoid metabolism and pathways by qRT-PCT. First trimester-like trophoblasts (HTR-8/SVneo) were treated with either β-carotene or lycopene. RNAs were isolated and gene expression were analyzed by DNA microarrays. Results Human CTBs express retinoid metabolism and pathways-related genes, including Stra6, Lrat, Rdh5, Rdh10, Aldh1a1, Aldh1a2, Aldh1a3, Aldh8a1, Cyp26a1, and Cyp26b1, but not carotenoid metabolism genes, BCO1 and BCO2. Microarray analysis of placental gene expression profile revealed a total of 872 and 756 differentially expressed genes, respectively, compared to the control. Gene set enrichment analysis and functional annotation clustering was performed to characterize the genes differentially expressed in either β-carotene or lycopene-treated HTR-8/SVneo cells. Many known retinoid metabolism related genes and genes involved in regulation of retinoid signaling were found, and the expression profiles of these genes were markedly different in response to β-carotene treatments. Finally, the qRT-PCR and microarray analysis results showed similar gene expression patterns of carotenoid/retinoid metabolism and pathways. Conclusions These findings suggest that placental expression of genes involved in retinoid metabolism and transport in trophoblasts is critical for regulating retinoid homeostasis during placental and fetal development. Carotenoid exposure in early placental development, significantly modify the placenta gene expression related to retinoid pathways and maternal to fetal transfer. Funding Sources NIH HD421174.

scholarly journals A network regularized linear model to infer spatial expression pattern for single cells

2021 ◽  
Author(s):  
Chaohao Gu ◽  
Zhandong Liu
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Spatial Information ◽  
Expression Profiles ◽  
Single Cells ◽  
Expression Patterns ◽  
Capture Rate ◽  
Marker Genes ◽  
Spatial Expression ◽  
Cellular Expression

Abstract Spatial gene-expression is a crucial determinant of cell fate and behavior. Recent imaging and sequencing-technology advancements have enabled scientists to develop new tools that use spatial information to measure gene-expression at close to single-cell levels. Yet, while Fluorescence In-situ Hybridization (FISH) can quantify transcript numbers at single-cell resolution, it is limited to a small number of genes. Similarly, slide-seq was designed to measure spatial-expression profiles at the single-cell level but has a relatively low gene-capture rate. And although single-cell RNA-seq enables deep cellular gene-expression profiling, it loses spatial information during sample-collection. These major limitations have stymied these methods’ broader application in the field. To overcome spatio-omics technology’s limitations and better understand spatial patterns at single-cell resolution, we designed a computation algorithm that uses glmSMA to predict cell locations by integrating scRNA-seq data with a spatial-omics reference atlas. We treated cell-mapping as a convex optimization problem by minimizing the differences between cellular-expression profiles and location-expression profiles with an L1 regularization and graph Laplacian based L2 regularization to ensure a sparse and smooth mapping. We validated the mapping results by reconstructing spatial- expression patterns of well-known marker genes in complex tissues, like the mouse cerebellum and hippocampus. We used the biological literature to verify that the reconstructed patterns can recapitulate cell-type and anatomy structures. Our work thus far shows that, together, we can use glmSMA to accurately assign single cells to their original reference-atlas locations.

scholarly journals Identification of spatial co-expression patterns and intra-tissue heterogeneity in spatially resolved transcriptomics by region-specific denoising

2021 ◽  
Author(s):  
Linhua Wang ◽  
Zhandong Liu
Keyword(s):  
Gene Expression ◽  
Missing Values ◽  
Spatial Organization ◽  
Expression Profiles ◽  
New Technology ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Tissue Heterogeneity ◽  
Region Detection ◽  
Spatially Resolved

Abstract We are pleased to introduce a first-of-its-kind tool that combines in-silico region detection and missing value estimation for spatially resolved transcriptomics. Spatial transcriptomics by 10X Visium (ST) is a new technology used to dissect gene and cell spatial organization. Analyzing this new type of data has two main challenges: automatically annotating the major tissue regions and excessive zero values of gene expression due to high dropout rates. We developed a computational tool—MIST—that addresses both challenges by automatically identifying tissue regions and estimating missing gene-expression values for each detected region. We validated MIST detected regions across multiple datasets using manual annotation on the histological staining images as references. We also demonstrated that MIST can accurately recover ST’s missing values through hold-out experiments. Furthermore, we showed that MIST could identify intra-tissue heterogeneity and recover spatial gene-gene co-expression signals. We therefore strongly encourage using MIST before downstream ST analysis because it provides unbiased region annotations and enables accurately denoised spatial gene-expression profiles.

Conserved molecular portraits of bovine and human blastocysts as a consequence of the transition from maternal to embryonic control of gene expression

2007 ◽  
Vol 31 (2) ◽  
pp. 315-327 ◽  
Author(s):  
James Adjaye ◽  
Ralf Herwig ◽  
Thore C. Brink ◽  
Doris Herrmann ◽  
Boris Greber ◽  
...  
Keyword(s):  
Translational Control ◽  
Protein Modification ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Mammalian Development ◽  
Control Of Gene Expression ◽  
Expression Of Genes ◽  
Conserved Genes ◽  
Solid Foundation ◽  
Bovine Oocytes

The present study investigated mRNA expression profiles of bovine oocytes and blastocysts by using a cross-species hybridization approach employing an array consisting of 15,529 human cDNAs as probe, thus enabling the identification of conserved genes during human and bovine preimplantation development. Our analysis revealed 419 genes that were expressed in both oocytes and blastocysts. The expression of 1,324 genes was detected exclusively in the blastocyst, in contrast to 164 in the oocyte including a significant number of novel genes. Genes indicative for transcriptional and translational control ( ELAVL4, TACC3) were overexpressed in the oocyte, whereas cellular trafficking ( SLC2A14, SLC1A3), proteasome ( PSMA1, PSMB3), cell cycle ( BUB3, CCNE1, GSPT1), and protein modification and turnover ( TNK1, UBE3A) genes were found to be overexpressed in blastocysts. Transcripts implicated in chromatin remodeling were found in both oocytes ( NASP, SMARCA2) and blastocysts ( H2AFY, HDAC7A). The trophectodermal markers PSG2 and KRT18 were enriched 5- and 50-fold in the blastocyst. Pathway analysis revealed differential expression of genes involved in 107 distinct signaling and metabolic pathways. For example, phosphatidylinositol signaling and gluconeogenesis were prominent pathways identified in the blastocyst. Expression patterns in bovine and human blastocysts were to a large extent identical. This analysis compared the transcriptomes of bovine oocytes and blastocysts and provides a solid foundation for future studies on the first major differentiation events in blastocysts and identification of a set of markers indicative for regular mammalian development.

scholarly journals Spatiotemporal single-cell RNA sequencing of developing chicken hearts identifies interplay between cellular differentiation and morphogenesis

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Madhav Mantri ◽  
Gaetano J. Scuderi ◽  
Roozbeh Abedini-Nassab ◽  
Michael F. Z. Wang ◽  
David McKellar ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Cellular Differentiation ◽  
Spatial Organization ◽  
Spatial Information ◽  
Cellular Interactions ◽  
Chicken Heart ◽  
Spatially Resolved ◽  
Expression Of Genes ◽  
Single Cell Rna Sequencing

AbstractSingle-cell RNA sequencing is a powerful tool to study developmental biology but does not preserve spatial information about tissue morphology and cellular interactions. Here, we combine single-cell and spatial transcriptomics with algorithms for data integration to study the development of the chicken heart from the early to late four-chambered heart stage. We create a census of the diverse cellular lineages in developing hearts, their spatial organization, and their interactions during development. Spatial mapping of differentiation transitions in cardiac lineages defines transcriptional differences between epithelial and mesenchymal cells within the epicardial lineage. Using spatially resolved expression analysis, we identify anatomically restricted expression programs, including expression of genes implicated in congenital heart disease. Last, we discover a persistent enrichment of the small, secreted peptide, thymosin beta-4, throughout coronary vascular development. Overall, our study identifies an intricate interplay between cellular differentiation and morphogenesis.

scholarly journals Spatially Resolved Expression of Transposable Elements in Disease and Somatic Tissue with SpatialTE

2021 ◽  
Vol 22 (24) ◽  
pp. 13623
Author(s):  
Braulio Valdebenito-Maturana ◽  
Cristina Guatimosim ◽  
Mónica Alejandra Carrasco ◽  
Juan Carlos Tapia
Keyword(s):  
Gene Expression ◽  
Transposable Elements ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Somatic Tissue ◽  
Rna Seq ◽  
Spatially Resolved ◽  
Repetitive Nature ◽  
Study Gene Expression ◽  
Regulatory Functions

Spatial transcriptomics (ST) is transforming the way we can study gene expression and its regulation through position-specific resolution within tissues. However, as in bulk RNA-Seq, transposable elements (TEs) are not being studied due to their highly repetitive nature. In recent years, TEs have been recognized as important regulators of gene expression, and thus, TE expression analysis in a spatially resolved manner could further help to understand their role in gene regulation within tissues. We present SpatialTE, a tool to analyze TE expression from ST datasets and show its application in somatic and diseased tissues. The results indicate that TEs have spatially regulated expression patterns and that their expression profiles are spatially altered in ALS disease, indicating that TEs might perform differential regulatory functions within tissue organs. We have made SpatialTE publicly available as open-source software under an MIT license.

scholarly journals Remnants of ancestral larval eyes in an eyeless mollusk? Molecular characterization of photoreceptors in the scaphopod Antalis entalis

EvoDevo ◽  
2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Tim Wollesen ◽  
Carmel McDougall ◽  
Detlev Arendt
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Binding Domain ◽  
Animal Evolution ◽  
Protein Activation ◽  
Expression Of Genes ◽  
Similar Gene Expression Profile ◽  
And Function

Abstract Background Eyes have evolved and been lost multiple times during animal evolution, however, the process of eye loss has only been reconstructed in a few cases. Mollusks exhibit eyes as varied as the octopod camera eye or the gastropod cup eye and are ideal systems for studying the evolution of eyes, photoreceptors, and opsins. Results Here, we identify genes related to photoreceptor formation and function in an eyeless conchiferan mollusk, the scaphopod Antalis entalis, and investigate their spatial and temporal expression patterns during development. Our study reveals that the scaphopod early mid-stage trochophore larva has putative photoreceptors in a similar location and with a similar gene expression profile as the trochophore of polyplacophoran mollusks. The apical and post-trochal putative photoreceptors appear to co-express go-opsin, six1/2, myoV, and eya, while expression domains in the posterior foot and pavilion (posterior mantle opening) show co-expression of several other candidate genes but not go-opsin. Sequence analysis reveals that the scaphopod Go-opsin amino acid sequence lacks the functionally important lysine (K296; Schiff base) in the retinal-binding domain, but has not accumulated nonsense mutations and still exhibits the canonical G-protein activation domain. Conclusions The scaphopod Go-opsin sequence reported here is the only known example of a bilaterian opsin that lacks lysine K296 in the retinal-binding domain. Although this may render the Go-opsin unable to detect light, the protein may still perform sensory functions. The location, innervation, development, and gene expression profiles of the scaphopod and polyplacophoran apical and post-trochal photoreceptors suggest that they are homologous, even though the scaphopod post-trochal photoreceptors have degenerated. This indicates that post-trochal eyes are not a polyplacophoran apomorphy but likely a molluscan synapomorphy lost in other mollusks. Scaphopod eye degeneration is probably a result of the transition to an infaunal life history and is reflected in the likely functional degeneration of Go-opsin, the loss of photoreceptor shielding pigments, and the scarce expression of genes involved in phototransduction and eye development. Our results emphasize the importance of studying a phylogenetically broad range of taxa to infer the mechanisms and direction of body plan evolution.

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