Academic literature on the topic 'Spatial transcriptomic'
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Journal articles on the topic "Spatial transcriptomic"
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Li, Youcheng, Leann Lac, Qian Liu, and Pingzhao Hu. "ST-CellSeg: Cell segmentation for imaging-based spatial transcriptomics using multi-scale manifold learning." PLOS Computational Biology 20, no. 6 (June 27, 2024): e1012254. http://dx.doi.org/10.1371/journal.pcbi.1012254.
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Spatial transcriptomics has gained popularity over the past decade due to its ability to evaluate transcriptome data while preserving spatial information. Cell segmentation is a crucial step in spatial transcriptomic analysis, as it enables the avoidance of unpredictable tissue disentanglement steps. Although high-quality cell segmentation algorithms can aid in the extraction of valuable data, traditional methods are frequently non-spatial, do not account for spatial information efficiently, and perform poorly when confronted with the problem of spatial transcriptome cell segmentation with varying shapes. In this study, we propose ST-CellSeg, an image-based machine learning method for spatial transcriptomics that uses manifold for cell segmentation and is novel in its consideration of multi-scale information. We first construct a fully connected graph which acts as a spatial transcriptomic manifold. Using multi-scale data, we then determine the low-dimensional spatial probability distribution representation for cell segmentation. Using the adjusted Rand index (ARI), normalized mutual information (NMI), and Silhouette coefficient (SC) as model performance measures, the proposed algorithm significantly outperforms baseline models in selected datasets and is efficient in computational complexity.
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Chen, Tsai-Ying, Li You, Jose Angelito U. Hardillo, and Miao-Ping Chien. "Spatial Transcriptomic Technologies." Cells 12, no. 16 (August 10, 2023): 2042. http://dx.doi.org/10.3390/cells12162042.
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Spatial transcriptomic technologies enable measurement of expression levels of genes systematically throughout tissue space, deepening our understanding of cellular organizations and interactions within tissues as well as illuminating biological insights in neuroscience, developmental biology and a range of diseases, including cancer. A variety of spatial technologies have been developed and/or commercialized, differing in spatial resolution, sensitivity, multiplexing capability, throughput and coverage. In this paper, we review key enabling spatial transcriptomic technologies and their applications as well as the perspective of the techniques and new emerging technologies that are developed to address current limitations of spatial methodologies. In addition, we describe how spatial transcriptomics data can be integrated with other omics modalities, complementing other methods in deciphering cellar interactions and phenotypes within tissues as well as providing novel insight into tissue organization.
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Lv, Zhuo, Shuaijun Jiang, Shuxin Kong, Xu Zhang, Jiahui Yue, Wanqi Zhao, Long Li, and Shuyan Lin. "Advances in Single-Cell Transcriptome Sequencing and Spatial Transcriptome Sequencing in Plants." Plants 13, no. 12 (June 18, 2024): 1679. http://dx.doi.org/10.3390/plants13121679.
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“Omics” typically involves exploration of the structure and function of the entire composition of a biological system at a specific level using high-throughput analytical methods to probe and analyze large amounts of data, including genomics, transcriptomics, proteomics, and metabolomics, among other types. Genomics characterizes and quantifies all genes of an organism collectively, studying their interrelationships and their impacts on the organism. However, conventional transcriptomic sequencing techniques target population cells, and their results only reflect the average expression levels of genes in population cells, as they are unable to reveal the gene expression heterogeneity and spatial heterogeneity among individual cells, thus masking the expression specificity between different cells. Single-cell transcriptomic sequencing and spatial transcriptomic sequencing techniques analyze the transcriptome of individual cells in plant or animal tissues, enabling the understanding of each cell’s metabolites and expressed genes. Consequently, statistical analysis of the corresponding tissues can be performed, with the purpose of achieving cell classification, evolutionary growth, and physiological and pathological analyses. This article provides an overview of the research progress in plant single-cell and spatial transcriptomics, as well as their applications and challenges in plants. Furthermore, prospects for the development of single-cell and spatial transcriptomics are proposed.
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Gorbunova, Vera. "COMPARATIVE TRANSCRIPTOMIC OF LONGEVITY." Innovation in Aging 7, Supplement_1 (December 1, 2023): 432. http://dx.doi.org/10.1093/geroni/igad104.1423.
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Abstract Transcriptome analysis provides a nuanced view into the changes that occur in cells and tissues. Transcriptome changes rapidly and reproducibly in response to physiological influences and environmental insults. Recent years have seen an exponential increase in transcriptome data at bulk, single cell and spatial resolution that allows insights into the mechanisms and regulatory pathways of aging and longevity. In this session Drs. Gorbunova (University of Rochester) and Gladyshev (Harvard Medical School) will discuss comparative transcriptomics of longevity across species with diverse lifespans that revealed unique signatures of longevity and the integration of transcriptome and proteome data. Dr. Gladyshev will discuss development of transcriptomic clocks of measuring biological aging. Dr. Artyomov will discuss single-cell resolution approaches to reveal aspects of immune aging in humans, and Dr. Palovics will present the use of transcriptomics to understand rejuvenating effects of heterochronic parabiosis.
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Callaway, Edward M., Hong-Wei Dong, Joseph R. Ecker, Michael J. Hawrylycz, Z. Josh Huang, Ed S. Lein, John Ngai, et al. "A multimodal cell census and atlas of the mammalian primary motor cortex." Nature 598, no. 7879 (October 6, 2021): 86–102. http://dx.doi.org/10.1038/s41586-021-03950-0.
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AbstractHere we report the generation of a multimodal cell census and atlas of the mammalian primary motor cortex as the initial product of the BRAIN Initiative Cell Census Network (BICCN). This was achieved by coordinated large-scale analyses of single-cell transcriptomes, chromatin accessibility, DNA methylomes, spatially resolved single-cell transcriptomes, morphological and electrophysiological properties and cellular resolution input–output mapping, integrated through cross-modal computational analysis. Our results advance the collective knowledge and understanding of brain cell-type organization1–5. First, our study reveals a unified molecular genetic landscape of cortical cell types that integrates their transcriptome, open chromatin and DNA methylation maps. Second, cross-species analysis achieves a consensus taxonomy of transcriptomic types and their hierarchical organization that is conserved from mouse to marmoset and human. Third, in situ single-cell transcriptomics provides a spatially resolved cell-type atlas of the motor cortex. Fourth, cross-modal analysis provides compelling evidence for the transcriptomic, epigenomic and gene regulatory basis of neuronal phenotypes such as their physiological and anatomical properties, demonstrating the biological validity and genomic underpinning of neuron types. We further present an extensive genetic toolset for targeting glutamatergic neuron types towards linking their molecular and developmental identity to their circuit function. Together, our results establish a unifying and mechanistic framework of neuronal cell-type organization that integrates multi-layered molecular genetic and spatial information with multi-faceted phenotypic properties.
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Adabbo, Bruno, Simona Migliozzi, Luciano Garofano, Young Taek Oh, Sakir H. Gultekin, Fulvio D'Angelo, Evan R. Roberts, et al. "EPCO-27. RECONSTRUCTION OF THE SPATIAL ECOSYSTEM OF GLIOBLASTOMA REVEALS RECURRENT RELATIONSHIPS BETWEEN TUMOR CELL STATES AND TUMOR MICROENVIRONMENT." Neuro-Oncology 25, Supplement_5 (November 1, 2023): v129. http://dx.doi.org/10.1093/neuonc/noad179.0490.
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Abstract Glioblastoma multiforme (GBM) is the most aggressive form of primary brain tumor, with no curative treatment options. Multiple studies have characterized at single cell resolution the GBM as being composed of transcriptional cell states interconnected with components in the tumor immune microenvironment (TME). Our group proposed and validated the first single cell guided functional classification of GBM in four tumor-intrinsic cell states which informed clinical outcome and delivered therapeutic options. However, single cell technologies lack the spatial relationships among the cell states of GBM and between GBM cell states and TME. Spatially resolved transcriptomic technologies are emerging as powerful tools to reconstruct the spatial architecture of a tissue. We performed spatial transcriptomics of multicellular regions of interest (ROI) in 8 IDH wild-type GBM with both CosMx Spatial Molecular Imager, which analyzes 1,000 RNA probes and 64 proteins at single cell resolution, and GeoMx Digital Spatial Profiler which profiles the whole transcriptome (~18,000 genes) at ROI resolution. We integrated the two platforms to define single cell states and non-malignant cells and developed a computational deconvolution approach for CosMx spatial data which utilized GeoMx ROI resolved transcriptomic profiles as a-priori information to predict cell type abundances. Spatial deconvolution of CosMx derived single cells revealed spatial segregation of the tumor cell clones and cellular states and highlighted recurrent patterns of cell states, distinct TME cell types associated with coherent histopathological features across multiple samples. Our studies established a scalable approach to resolve the transcriptional heterogeneity of GBM and reconstruct the architecture of GBM cell states and tumor microenvironment.
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He, Jiang, Bin Wang, Justin He, Renchao Chen, Benjamin Patterson, Sudhir Tattikota, Timothy Wiggin, et al. "Abstract LB333: Improved spatially resolved single-cell transcriptomic imaging in archival tissues with MERSCOPE." Cancer Research 84, no. 7_Supplement (April 5, 2024): LB333. http://dx.doi.org/10.1158/1538-7445.am2024-lb333.
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Abstract The advent of spatial transcriptomics has enabled a revolution in how complex tissues are studied. However, samples with lower quality RNA due to degradation, protein crosslinking, or high RNase content remain challenging for spatial transcriptomic measurement. In particular, formalin fixed, paraffin embedded (FFPE) tissues are the most widely used sample types in clinical and molecular diagnosis, yet they are notoriously difficult for single-cell transcriptomic analysis. To accurately profile the gene expression in FFPE samples in situ, a spatial transcriptomics technique with high detection efficiency and single molecule resolution is required. The Vizgen® MERSCOPE® Platform for spatial genomics is built on Multiplexed Error Robust in situ Hybridization (MERFISH) technology and directly profiles the transcriptome of intact tissues with high sensitivity in high-quality samples. Here we present an updated workflow to perform MERFISH in low and high-quality samples. We demonstrated its application in more than 5 FFPE sample types from mouse and human, including archival samples. For each tissue type, hundreds of thousands of cells were captured using the updated MERSCOPE Platform workflow, generating 100s million counts and their spatial information for profiled genes in each sample. The updated workflow involves streamlined sample preparation and chemistry optimization to improve sensitivity. MERSCOPE accurately profiled gene expression in situ and mapped cell types in archival human samples across a range of low and high RNA qualities. We compared the performance of MERSCOPE imaging using the updated protocol to the previous version and observed a significant increase in gene counts per 100 micron2 of tissue. We also demonstrated increased reproducibility between replicates with the streamlined workflow and chemistry. Furthermore, we demonstrated the updated workflow is compatible with simultaneous protein-based cell boundary staining. Finally, we constructed a spatially resolved single-cell atlas across low-quality archival breast and lung tumor types, mapped and cataloged different cell types within the tumor microenvironment, and systematically characterized the gene expression among cells. Spatially resolved transcriptomic profiling of low-quality samples at single-cell level provides enormous opportunities in cancer research. These improvements will enable new genomic inquiries into previously intractable tissues like FFPE, leading to new biological insights into cancer progression. Citation Format: Jiang He, Bin Wang, Justin He, Renchao Chen, Benjamin Patterson, Sudhir Tattikota, Timothy Wiggin, Lizi Maziashvili, Peter Reinhold, Manisha Ray, George Emanuel. Improved spatially resolved single-cell transcriptomic imaging in archival tissues with MERSCOPE [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB333.
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Jiang, Peng. "Abstract IA002: Inference of intercellular signaling activities in tumor spatial and single-cell transcriptomics, with applications in identifying cancer immunotherapy targets." Molecular Cancer Therapeutics 22, no. 12_Supplement (December 1, 2023): IA002. http://dx.doi.org/10.1158/1535-7163.targ-23-ia002.
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Abstract My talk will present three computational frameworks we developed to study cytokine signaling activities and cell-cell communications during the antitumor immune response, using tumor single-cell and spatial transcriptomics. The basic immunology tool to study cytokine signaling mostly measures cytokine release, which is transient and does not represent downstream target activities. Therefore, we first developed the CytoSig platform, providing a database of target genes modulated by cytokines and a predictive model of cytokine signaling cascades from transcriptomic profiles. We collected 20,591 transcriptome profiles for human cytokine, chemokine, and growth factor responses. This atlas of transcriptional patterns induced by cytokines enabled the reliable prediction of signaling activities in distinct cell populations in infectious diseases, chronic inflammation, and cancer using bulk and single-cell transcriptomic data. CytoSig revealed previously unidentified roles of many cytokines, such as BMP6 as an anti-inflammatory factor. Then, based on CytoSig, we developed Tres, a computational model utilizing single-cell transcriptomic data to identify signatures of T cells that are resilient to immunosuppressive signals, such as TGF-β1, TRAIL, and prostaglandin E2. Tres reliably predicts clinical responses to immunotherapy in multiple cancer types using bulk T cell transcriptomic data from pre-treatment patient tumors or infusion/pre-manufacture samples for cellular immunotherapies. Further, Tres identified FIBP as a candidate immunotherapy target to potentiate adoptive cell therapy efficacies. FIBP knockout in T cells enhanced adoptive cell therapy by down-regulating T cells' cholesterol metabolism. Last, I will briefly show our SpaCET framework for deconvolving cell fractions and identifying cell-cell interactions in tumor spatial transcriptomics data. SpaCET resolved several challenges in spatial transcriptomics analysis that previous methods did not address sufficiently. Through coupling cell fractions with ligand-receptor co-expression analysis, SpaCET reveals that intercellular interactions tend to be located at the tumor-immune boundaries. Citation Format: Peng Jiang. Inference of intercellular signaling activities in tumor spatial and single-cell transcriptomics, with applications in identifying cancer immunotherapy targets [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2023 Oct 11-15; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2023;22(12 Suppl):Abstract nr IA002.
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Ali, Abdullah Mahmood, and Azra Raza. "scRNAseq and High-Throughput Spatial Analysis of Tumor and Normal Microenvironment in Solid Tumors Reveal a Possible Origin of Circulating Tumor Hybrid Cells." Cancers 16, no. 7 (April 8, 2024): 1444. http://dx.doi.org/10.3390/cancers16071444.
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Metastatic cancer is a leading cause of death in cancer patients worldwide. While circulating hybrid cells (CHCs) are implicated in metastatic spread, studies documenting their tissue origin remain sparse, with limited candidate approaches using one–two markers. Utilizing high-throughput single-cell and spatial transcriptomics, we identified tumor hybrid cells (THCs) co-expressing epithelial and macrophage markers and expressing a distinct transcriptome. Rarely, normal tissue showed these cells (NHCs), but their transcriptome was easily distinguishable from THCs. THCs with unique transcriptomes were observed in breast and colon cancers, suggesting this to be a generalizable phenomenon across cancer types. This study establishes a framework for HC identification in large datasets, providing compelling evidence for their tissue residence and offering comprehensive transcriptomic characterization. Furthermore, it sheds light on their differential function and identifies pathways that could explain their newly acquired invasive capabilities. THCs should be considered as potential therapeutic targets.
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He, Jiang, Justin He, Timothy Wiggin, Rob Foreman, Renchao Chen, Nicolas Fernandez, and George Emanuel. "Abstract 4195: Spatially resolved single cell transcriptomic profiling in formalin-fixed paraffin-embedded (FFPE) tissues." Cancer Research 83, no. 7_Supplement (April 4, 2023): 4195. http://dx.doi.org/10.1158/1538-7445.am2023-4195.
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Abstract Formalin-fixed paraffin-embedded (FFPE) tissues are the most widely used clinical sample types in histology and molecular diagnosis, but these samples are often challenging for single-cell transcriptomic analysis due to RNA degradation and protein crosslinking. A spatial transcriptomics technique with high detection efficiency and single molecule resolution is required in order to accurately profile the gene expression in FFPE samples in situ. Vizgen’s MERSCOPE platform, built on multiplexed error robust in situ hybridization MERFISH technology, directly profiles intact tissue’s transcriptome with subcellular spatial resolution. Here, we demonstrate the FFPE MERSCOPE workflow in tissues from 10 mouse and human samples, including archival clinical samples. In each sample, hundreds of thousands of cells were captured with >100 million transcript counts, generating detailed spatial transcriptomic data for the profiled genes in each sample. A comparison of FFPE and matched fresh frozen samples indicated that the FFPE workflow performs similarly in detection efficiency as compared to the fresh frozen protocol. We further demonstrated the MERSCOPE FFPE workflow is compatible with protein imaging by performing simultaneous protein-based cell boundary staining with MERFISH to accurately profile gene expression and map cell types in archival clinical human samples. Finally, we constructed a spatially resolved single cell atlas across eight major tumor types, mapped and cataloged different cell types within the tumor microenvironment and systematically characterized the gene expression among cells. This study demonstrates the potential for spatially resolved transcriptomic profiling of FFPE samples at single cell level to contribute to a wide range of biomedical research areas, including many applications to study human diseases. Citation Format: Jiang He, Justin He, Timothy Wiggin, Rob Foreman, Renchao Chen, Nicolas Fernandez, George Emanuel. Spatially resolved single cell transcriptomic profiling in formalin-fixed paraffin-embedded (FFPE) tissues. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4195.
Dissertations / Theses on the topic "Spatial transcriptomic"
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Larsson, Ludvig. "Optimization of UMI counting strategies for Spatial Transcriptomics." Thesis, KTH, Skolan för kemi, bioteknologi och hälsa (CBH), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-233838.
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Spatial Transcriptomics (ST) is a microarray-based RNA sequencing technology that allows for genome-wide transcriptome profiling of tissue sections with spatialresolution, which was published in Science by Ståhl and Salmén et al in 2016. Polyadenylated transcripts are captured on a microarray surface through hybridizationwith a barcoded DNA oligo that carries the information necessary to infer spatialposition and transcript uniqueness from the output sequencing reads. The ST protocolutilizes Unique Molecular Identifiers (UMIs) to remove PCR duplicates and obtain reliable estimates of gene counts. However, errors gradually accumulate in the UMIpool as a consequence of enzymatic conversion steps and these errors ought to be addressed computationally in data processing steps to produce reliable gene countestimates.In this thesis, we used ERCC reference RNAs and a set of custom-made DNA oligosas spike-ins in the ST protocol to explore sources of technical variation under controlled experimental conditions. An exploratory analysis of the spike-in data gave new insights into the chemistry which could guide future improvements of the protocol. We also developed a new strategy to bin read alignments before gene quantification and showed that this strategy produces a more reliable output. Finally, we developed an in silicosimulation of the ST library preparation to provide a framework that can be used toevaluate the performance of various computational processing strategies. The simulation was then used to benchmark a set of duplicate removal algorithms used toquantify gene expression.This master thesis project was carried out at SciLifeLab at the division of GeneTechnology under supervision of José Fernandez Navarro.Spatial Transcriptomics (ST) är en teknologi som utvecklades av Ståhl och Salmén etal (2016) och som används för att analysera RNA från vävnadssnitt. Metoden användersig av ett mikrochip som kan fånga upp polyadenylerade molekyler från vävnaden med hjälp av oligo(dT)-prober som är riggade på ytan. Varje yt-prob innehåller en positionsspecifiksekvens som kan användas för att bestämma från vilken position på ytan enRNA-molekyl fångats och ger därmed en möjlighet att analysera transkriptomet överhela vävnadssnittet. Genom att kombinera denna teknologi med högupplöst ljusfältsmikroskopiär det möjligt att skapa en tvådimensionell representation av genuttrycksom direkt kan kopplas till vävnadens morfologi. På varje DNA-oligo finns förutompositions-specifika sekvenser dessutom en kortare sekvens, en så kallad UMI somanvänds för att avlägsna PCR-duplikat. Dessa sekvenser kan signifikant förbättra estimaten av genuttryck, men är känsliga för mutationer och fel som uppstår under de flertalet enzymatiska reaktioner som utnyttjas i ST-protokollet. Fel som uppstår i UMIsekvensen hanteras med data-baserade algoritmer och kräver en noggrann strategi för att generera en precis biologisk representation.I detta projekt användes ett sett av standardiserade RNA-molekyler (ERCC) samtskräddarsydda DNA-oligos som ett substitut för biologiskt material för att utvärderakällor till teknisk variation som har en direkt inverkan på estimeringen av genuttryck.Vi utvecklade även en ny strategi för att gruppera RNA-sekvenser och visar hur denna strategi producerar mer pålitliga resultat. Slutligen presenterar vi en in silico-simuleringav hela ST-metoden som kan användas som ett ramverk för att testa nya algoritmer för att kvantifiera genuttryck. Med detta ramverk utförde vi en riktmärkning av olikaalgoritmer som används för att eliminera PCR-duplikat och selekterade därefter en robust algoritm baserat på resultaten från simuleringen.Detta projekt utfördes på SciLifeLab på avdelningen för genteknologi underhandledning av José Fernandez Navarro.
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Van, Leen Eric. "On the morphogenesis of the D. melanogaster pupa : a study on gene patterning and tissue folding." Electronic Thesis or Diss., Sorbonne université, 2020. http://www.theses.fr/2020SORUS387.
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Au cours du développement, la coordination des comportements cellulaires est essentielle à la formation d’organes complexes et fonctionnels. L’analyse de ces processus cellulaire est essentielle pour comprendre comment les tissues se forment au cours du développement. Pour ce faire, il est tout d’abord primordial d’identifier les gènes dont l’expression est corrélée avec chacun de ces processus cellulaires. Avec pour modèle la formation de l’épithélium dorsal (le notum) de la pupe de drosophile, mon travail de thèse a visé à identifier les mécanismes moléculaires qui gouvernent la régulation spatiale de la morphogenèse de l’échelle cellulaire à l’échelle de l’organisme. Dans un premier temps, j’ai mis en œuvre une analyse de transcriptomique spatiale qui m’a permis d’identifier de nouveaux gènes impliqués dans la morphogenèse du notum. Dans un second temps, j’ai développé un microscope confocal rotatif avec l’aide de la plateforme d’imagerie de l’Institut Curie. En appliquant cette nouvelle méthode au cours du développement de la pupe jusqu’au stade adulte, j’ai pu observer la morphogenèse de l’aile et du notum de manière simultanée. J’ai ainsi identifié un nouveau mouvement morphogénétique du notum entre 45-50 hAPF qui semble indépendant de la morphogenèse de l’aile dans le temps et dans l’espace. Enfin j’ai montré que ce mouvement est contrôlée par l’expression de sérine-protéases qui libèrent l’attachement de l’épithélium à la cuticule. Ce travail de thèse représente un apport important à une compréhension fine et intégrée de la régulation de la morphogenèse et de la coordination des dynamiques cellulaires au cours du développementIn order to achieve complex shapes during development, multicellular organisms need to coordinate cellular behaviors to form complex and functional organs. Identifying genes that are expressed in patterns that correlate with cellular processes is therefore primordial. Using the dorsal epithelium (the notum) of drosophila pupa as a model, my thesis aimed at uncovering the molecular mechanisms which control the spatial regulation of morphogenesis at the cell and tissue scale. First, I developed spatial transcriptomics which enabled the identification of new expression patterns involved in notum morphogenesis. Second, I developed, in collaboration with the imaging platform of Institut Curie, Rotating Sample Confocal Microscopy. Using this technique, I was able to simultaneously observe the morphogenesis of the notum, hinge and wing blade. This enabled the discovery of a new morphogenetic movement in the notum between 45-50hAPF. My results suggest that this extensive folding and elongation of the notum is independent of folding in the wing. Furthermore, I demonstrated that the expression of serine proteases regulate the attachment of the tissue to the cuticle which triggers the onset of the folding and determines the final shape of the tissue. Overall, this work increases our understanding of the spatial regulation of morphogenesis and contributes to the knowledge on how the extracellular matrix can regulate tissue shape
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Peiffer, Jason, Shail Kaushik, Hajime Sakai, Mario Arteaga-Vazquez, Nidia Sanchez-Leon, Hassan Ghazal, Jean Vielle-Calzada, and Blake Meyers. "A spatial dissection of the Arabidopsis floral transcriptome by MPSS." BioMed Central, 2008. http://hdl.handle.net/10150/610079.
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BACKGROUND:We have further characterized floral organ-localized gene expression in the inflorescence of Arabidopsis thaliana by comparison of massively parallel signature sequencing (MPSS) data. Six libraries of RNA sequence tags from immature inflorescence tissues were constructed and matched to their respective loci in the annotated Arabidopsis genome. These signature libraries survey the floral transcriptome of wild-type tissue as well as the floral homeotic mutants, apetala1, apetala3, agamous, a superman/apetala1 double mutant, and differentiated ovules dissected from the gynoecia of wild-type inflorescences. Comparing and contrasting these MPSS floral expression libraries enabled demarcation of transcripts enriched in the petals, stamens, stigma-style, gynoecia, and those with predicted enrichment within the sepal/sepal-petals, petal-stamens, or gynoecia-stamens.RESULTS:By comparison of expression libraries, a total of 572 genes were found to have organ-enriched expression within the inflorescence. The bulk of characterized organ-enriched transcript diversity was noted in the gynoecia and stamens, whereas fewer genes demonstrated sepal or petal-localized expression. Validation of the computational analyses was performed by comparison with previously published expression data, in situ hybridizations, promoter-reporter fusions, and reverse transcription PCR. A number of well-characterized genes were accurately delineated within our system of transcript filtration. Moreover, empirical validations confirm MPSS predictions for several genes with previously uncharacterized expression patterns.CONCLUSION:This extensive MPSS analysis confirms and supplements prior microarray floral expression studies and illustrates the utility of sequence survey-based expression analysis in functional genomics. Spatial floral expression data accrued by MPSS and similar methods will be advantageous in the elucidation of more comprehensive genetic regulatory networks governing floral development.
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Jestin, Martin. "Modifications du microenvironnement stromal après irradiation localisée du côlon : identification de voies moléculaires pour optimiser le processus de régénération épithéliale." Electronic Thesis or Diss., Sorbonne université, 2024. https://accesdistant.sorbonne-universite.fr/login?url=https://theses-intra.sorbonne-universite.fr/2024SORUS165.pdf.
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Les cancers pelviens ont une prévalence élevée et sont principalement traités par radiothérapie. Si elle permet un contrôle de la tumeur, la radiothérapie peut également provoquer des lésions aux tissus sains environnants, entrainant des complications invalidantes définies comme une maladie à part entière, la «Pelvic Radiation Disease» ou PRD. Aujourd'hui, il n'existe pas de traitement curatif pour cette pathologie fibrosante. Ce projet vise à étudier le microenvironnement du côlon après irradiation afin d'identifier, à terme, des cibles thérapeutiques pour la prise en charge des séquelles coliques de la PRD. Pour ce projet, un modèle de souris développant des lésions coliques fibrosantes similaires à celles observées chez les patients atteints de PRD a été mis au point. Il consiste en une irradiation colorectale localisée en dose unique de 26Gy. Nous avons défini 2 temps d'étude post-irradiation : à 2 semaines afin d'étudier les effets aigus de l'irradiation ainsi que le processus de régénération et 12 semaines pour étudier la fibrose. Des études histologiques ont permis de caractériser les lésions muqueuses avec un ulcère profond à 2 semaines, et des remaniements fibreux à 12 semaines. Aux 2 temps étudiés, un processus de prolifération accru et désordonné a été observé ainsi qu'un déficit en protéines de jonctions épithéliales suggérant un défaut de la fonction de barrière. Nous avons démontré l'impact du microenvironnement colique irradié sur les processus de prolifération et de différenciation épithélial par un système de coculture avec des organoïdes coliques suivi par vidéo-microscopie. Nos résultats ont permis de valider les observations in vivo, à savoir une prolifération accrue des organoïdes en présence de stroma issus de souris 12 semaines post-irradiation. Afin de caractériser les cellules mésenchymateuses du stroma après irradiation, des expériences de séquençage d'ARN sur cellule unique (à partir de cellules coliques triées EpCAM-CD45- et issues de colon total) et de transcriptomique spatiale ont été réalisées. Elles ont mis en évidence un nouveau marqueur, Edil3, spécifique de la population stromale majeure du côlon. Ce nouveau marqueur nous a permis de mieux caractériser cette population cellulaire en termes de fonction et de localisation au niveau du côlon sain. Nous avons proposé de la nommer Mésitocytes. Au temps précoce, nous avons établi que cette population pouvait se différencier vers un profil pro-inflammatoire appelé « IAF » pour «Inflammation-Associated Fibroblasts». Nous avons également observé une augmentation de l'expression de transcrits impliqués dans des fonctions cruciales telles que l'homéostasie épithéliale, l'angiogenèse et l'inflammation par la majorité des cellules mésenchymateuses. Les résultats montrent l'importance des signaux moléculaires prolifératifs issus des cellules endothéliales lymphatiques et des cellules musculaires lisses, notamment Grem-1. L'analyse de la phase chronique après irradiation, confirme l'augmentation des signaux prolifératifs par les cellules du stroma. De plus, un nouveau type de cellules fibroblastique associé à la fibrose a été observé, caractérisé par profil transcriptionnel différent des IAF observés en phase précoce. L'étude de l'impact de l'irradiation sur le compartiment épithélial a mis en évidence des modifications importantes au niveau de la population de colonocytes et l'émergence de cellules épithéliales avec un phénotype « revival », déjà décrit dans la littérature. De façon intéressante, ces populations ont des localisations spécifiques au niveau des cryptes en régénération. Nous avons également établi l'importance de gènes tels que Lypd8 et Anxa1 dans la progression des cellules épithéliales proliférantes vers un phénotype «revival». Des observations intéressantes issues des analyses de transcriptomique spatiale permettent également d'émettre des hypothèses quant au rôle des cellules immunitaires dans le processus de régénération épithélialPelvic cancers are highly prevalent and are mainly treated with radiotherapy. While radiation therapy may control the tumor, it can also cause damage to surrounding healthy tissue, leading to disabling complications defined as a disease “pelvic radiation disease” (PRD). Currently, there is no curative treatment for this fibrosing pathology. The aims of this project are to study the colonic microenvironment after irradiation with a view to identify new therapeutic targets to improve the management of the colonic sequelae of PRD. For this project, a mouse model developing fibrosing colonic lesions similar to those observed in PRD patients was developed. It consists of localized colorectal irradiation with a single dose of 26Gy. We defined 2 post-irradiation study periods: 2 weeks to study the acute effects of irradiation and the regeneration process, and 12 weeks to study fibrosis. Histological studies characterized the mucosal lesions, with a deep ulcer at 2 weeks and fibrous remodeling at 12 weeks. At the 2 time points studied, an increased and disorganized proliferative process was observed, as well as a deficit in epithelial junction proteins, suggesting a defect in barrier function. We demonstrated the impact of the irradiated colonic microenvironment on epithelial proliferation and differentiation processes using a co-culture system with colonic organoids monitored by video microscopy. Our results validated in vivo observations of increased organoid proliferation in the presence of stroma derived from mice 12 weeks post-irradiation.To characterize stromal mesenchymal cells after irradiation, single-cell RNA sequencing experiments (using EpCAM-CD45-sorted colonic cells and from whole colon) and spatial transcriptomics were performed. They revealed a new marker, Edil3, specific for the major stromal population of the colon. This new marker allowed us to better characterize this cell population in terms of function and localization in the healthy colon. We proposed to call them mesitocytes. In the early stages, we found that this population could differentiate towards a pro-inflammatory profile called "IAF" for "Inflammation-Associated Fibroblasts". We also observed increased expression of transcripts involved in critical functions such as epithelial homeostasis, angiogenesis and inflammation by the majority of mesenchymal cells. The results demonstrate the importance of proliferative molecular signals from lymphatic endothelial cells and smooth muscle cells, particularly Grem-1. Analysis of the chronic phase after irradiation confirms the increase in proliferative signals from stromal cells. In addition, a new fibroblast cell type associated with fibrosis was observed, characterized by a transcriptional profile different from that of the IAF observed in the early phase. The study of the effects of irradiation on the epithelial compartment revealed significant changes in the colonocyte population and the appearance of epithelial cells with a "revival" phenotype, already described in the literature. Interestingly, these populations have specific localizations in regenerating crypts. We also established the importance of genes such as Lypd8 and Anxa1 in the progression of proliferating epithelial cells towards a "revival" phenotype. Interesting observations from spatial transcriptomic analyses also allow us to hypothesize the role of immune cells in the epithelial regeneration process
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Currás, alonso Sandra. "Lung responses to radiation injury at the single cell level." Electronic Thesis or Diss., Université Paris sciences et lettres, 2021. http://www.theses.fr/2021UPSLS060.
Full textAbstract:
La radiothérapie constitue une option thérapeutique majeure pour le traitement du cancer du poumon. Néanmoins, la radiothérapie induit chez environ 5 à 20 % des patients traités des toxicités pulmonaires irréversibles précoces et tardives, telles que la pneumonite aiguë ou la fibrose pulmonaire induite par la radiothérapie (FPRI). La FPRI est caractérisée par une destruction progressive et irréversible de l'architecture alvéolaire avec perturbation des échanges gazeux conduisant à la mort des patients. Bien que l'ordre des événements moléculaires et cellulaires dans la progression vers la FPRI soit un aspect pathogénique clé de la maladie, leur coordination dans l'espace et le temps reste largement inexplorée. L'objectif principal de ce projet est d'étudier la dynamique dans le temps et l'espace des mécanismes cellulaires et moléculaires qui conduisent à la fibrose pulmonaire après l’irradiation. La combinaison d'analyses single cell RNA sequencing (scRNAseq), pour étudier les réponses précoces et tardives à l’irradiation au niveau d'une seule cellule, et de la single molecule (sm) FISH, pour cartographier les types de cellules spécifiques dans le tissu, a fourni des informations sur la façon dont le tissu pulmonaire se réorganise et évolue progressivement vers un état de fibrose. Les résultats de ce projet mettent en lumière les processus moléculaires induits par l’irradiation, tels que la régénération pulmonaire, la transdifférenciation des cellules épithéliales alvéolaires, l’EMT, l’inflammation et la sénescence dans les compartiments pulmonaires impliqués dans la régénération du tissue, la cicatrisation et la fibrose. Comprendre quels sont les mécanismes à l'origine de la FPRI permettra de trouver de nouveaux traitements thérapeutiques pour améliorer les soins et la qualité de vie des patientsA major therapeutic option for lung cancer treatment is radiotherapy. Nevertheless, around 5-20% of the patients treated with radiation therapy suffer from early and late irreversible lung toxicities, such as acute pneumonitis or radiotherapy induced pulmonary fibrosis (RIPF). RIPF is characterized by progressive and irreversible destruction of the alveolar architecture with disruption of gas exchange and terminal failure. Although the order of molecular and cellular events in the progression towards RIPF is a key pathogenic aspect of the disease, their coordination in space and time remains largely unexplored. The overarching aim of this project is to study the dynamics in time and space of the cellular and molecular mechanisms that lead to lung fibrosis after ionizing radiation (IR). The combination of single cell RNA sequencing (scRNAseq) analyses, to study early and late responses to injury at the single cell level, and single molecule (sm) FISH, to map specific cell types in tissue, have provided information on how mouse and human lung tissues responds to radiation injury. The results of this project highlight the dynamics on specific radiation-induced processes, such as regeneration, transdifferentiation, EMT, inflammation and senescence in the main compartments of the lung that are known to play a major role in tissue repair, regeneration and fibrosis. Importantly, this study points at a senescence process affecting specifically the endothelial cell compartment over the course of fibrosis after fibrogenic doses of IR. Understanding what are the mechanisms causing this disease will pave the way to new therapeutic options that may improve patients’ treatments and their quality of life
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Lötstedt, Britta. "Towards spatial host-microbiome profiling." Licentiate thesis, KTH, Genteknologi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-289384.
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Sequencing technologies and applications have pushed the limits and enabled novel studies of biological mechanisms, evolutionary relationships and communication networks between cells. The technical developments leading to single cell RNA-sequencing have enabled detection of rare cell populations while spatial resolution added insights into larger biological environments, like tissues and organs. Massively parallel sequencing has paved the way for integrated high-throughput analyses including that of studying gene expression, protein expression and mapping of microbial communities. This thesis starts with an introduction describing the technical and biological advancements made in recent years with focus on spatially resolved approaches. Then, a summary of recent accomplishments is presented, which enabled ongoing work in a novel field of spatial hostmicrobiome profiling. Lastly, the concluding remarks include both a future perspective and a short reflection on the current developments in the spatial multi-omics field. 16S sequencing is often used for taxonomic classification of bacteria. In Paper I, this sequencing technique was used to study the aerodigestive microbiome in pediatric lung transplant recipients. Many of these patients regretfully reject the organ after transplant, but the underlying cause is, in many cases, unknown. In this paper, multiple factors influencing rejection were examined including that of the aerodigestive microbiome. Pediatric lung transplant recipients often suffer from gastrointestinal dysmotility and the focus of this study was also to analyze changes in the microbiome in relation to irregular gastric muscle movements. The results showed that lung transplant recipients had, in general, lower microbial diversity in the gastric fluid and throat and also that the microbial overlap between lung and gastric sampling sites was significantly less in transplant recipients compared to controls. In addition, gastrointestinal dysmotility was shown to influence the gastric microbiome in lung transplant recipients, but, given the small sample size available in this study, the correlation to patient outcome could not be examined. Integrated analysis of the transcriptome and the antibody-based proteome in the same tissue section was enabled using the method developed in Paper II. Spatial Multi- Omics (SM-Omics) uses a barcoded glass array to capture mRNA and antibody-based expression of selected proteins in the same section. The antibody-based profiling of the tissue section was enabled by either immunofluorescence or DNA-barcoded antibodies that were then decoded by sequencing. The protocol was scaled-up using an automated liquidhandling system. Using this method, simultaneous profiling of the transcriptome and multiplexed protein values was determined in both the mouse brain cortex and mouse spleen. Results showed a high correlation in spatial pattern between gene expression and antibody measurements, independently of the antibody labelling technique. SM-Omics generates a high-plex multi-omics characterization of the tissue in a high throughput manner while exhibiting low technical variation.Tekniker och applikationer som använder sekvensering har flyttat fram gränsernaoch tillåtit nya undersökningar av biologiska mekanismer, evolutionära släktskap ochkommunikationsnätverk mellan celler. De tekniska utvecklingarna som har lett fram tillRNA-sekvensering av enskilda celler har möjliggjort upptäckten av sällsynta cellpopulationer medan den rumsliga upplösningen har inneburit en ökad förståelse av störrebiologiska miljöer, såsom vävnader och organ. Massively parallel sequencing har banat vägför integrerade analyser med hög kapacitet, vilket inkluderar analys av genuttryck,proteinuttryck och kartläggning av bakteriella samhällen. Den här avhandlingen börjar meden introduktion som beskriver tekniska och biologiska framsteg som gjorts de senaste åren,med fokus på den rumsliga upplösningen. Sedan följer en summering av de senasteprestationerna som har möjliggjort det pågående arbetet i ett nytt fält som avhandlarrumslig profilering av bakterien och dess värd. Slutligen innehåller slutordet både ettframtida perspektiv samt en kort reflektion av den nuvarande utvecklingen inom fälten förrumslig mång-omik. 16S-sekvensering används ofta för att taxonomiskt klassificera bakterier. Dennasekvenseringsteknik användes i artikel I för att studera mikrobiomet i luft- ochmatspjälkningskanalen hos barn med transplanterad lunga. Dessvärre är det vanligt medavstötning av lungan efter transplantationen hos många av dessa patienter, men denunderliggande orsaken till avstötningen är, i många fall, okänd. I denna studie undersöktesflertalet faktorer, inklusive mikrobiomet i luft- och matspjälkningskanalen, som kan tänkaspåverka bortstötningen. Barn med transplanterad lunga lider ofta av störningar i magtarmkanalens rörelser och artikelns fokus var därmed även att analysera förändringar imikrobiomet i relation till dessa avvikande rörelser i mag-tarmkanalen. Resultatet visade attpatienter med transplanterad lunga generellt hade lägre bakteriell mångfald i magsaft ochhals, samt att det bakteriella överlappet mellan lunga och magsaft var signifikant mindre ipatienter med transplanterad lunga jämfört med kontrollerna. För övrigt visade det sig attstörningar i mag-tarmkanalens rörelser påverkade magsaftens mikrobiom hos patientermed transplanterad lunga, men på grund av studiens storlek på urvalet, kunde det inteundersökas hur detta korrelerade till utfallet hos patienterna. Integrerad analys av transkriptomet och antikroppsbaserad analys av proteomet isamma vävnadssnitt har möjliggjorts genom metoden som utvecklats i artikel II. SpatialMulti-Omics (SM-Omics) använder ett avkodningsbart mönster av korta DNA-segment påen glasyta för att fånga mRNA och antikroppsbaserat uttryck av utvalda proteiner frånsamma vävnadssnitt. Den antikroppsbaserade profileringen av vävnadssnittet uppnåddesgenom antingen immunofluorescens eller antikroppar märkta med DNA-segment somkunde avkodas genom sekvensering. Protokollet skalades upp genom ett automatiseratsystem för att behandla vätskor. Genom användning av denna metod kunde simultanprofilering av transkriptomet och flertalet proteiner uppnås i både hjärnbarken och mjältenhos en mus. Resultaten visade en hög korrelation i det rumsliga mönstret mellangenuttrycket och de antikroppsbaserade mätningarna, oberoende av hur antikropparnahade märkts. SM-Omics genererar en storskalig karaktärisering av vävnaden av flera omikermed hög kapacitet samtidigt som den har låg teknisk variation.
QC 2021-02-02
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Kaewsapsak, Pornchai. "Spatially-resolved transcriptomic mapping in live cells using peroxidase-mediated proximity biotinylation." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/113972.
Full textAbstract:
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Chemistry, 2017.Cataloged from PDF version of thesis.
Includes bibliographical references.
The spatial organization of RNA within cells is crucial for the regulation of a wide range of biological functions, spanning all kingdoms of life. However, a general understanding of RNA localization has been hindered by a lack of simple, high-throughput methods for mapping the transcriptomes of subcellular compartments. Here, we developed two methods, termed APEX-RIP and APEX-Seq. APEX-RIP combines peroxidase-catalyzed, spatially restricted in situ protein biotinylation with RNA-protein chemical crosslinking, while APEX-Seq utilizes peroxidase-catalyzed in situ biotinylation on RNA. We demonstrated that APEX-RIP can isolate RNAs from a variety of subcellular compartments, including the mitochondrial matrix, nucleus, bulk cytosol, and endoplasmic reticulum (ER) membrane, with higher specificity and coverage than conventional approaches. We furthermore identified candidate RNAs localized to mitochondria-ER junctions and nuclear lamina, two compartments that are recalcitrant to classical biochemical purification. Similarly, APEX-Seq can isolate RNAs from mitochondrial matrix, ER-associated RNAs, OMM-associated RNAs, and potentially other non-membrane bound compartments. We also revealed many non-coding RNA candidates at these sites. Since APEX-RIP and APEX-Seq are simple, versatile, and do not require special instrumentation, we envision their broad applications in a variety of biological contexts.
by Pornchai Kaewsapsak.
Ph. D.
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Mignardi, Marco. "In situ Sequencing : Methods for spatially-resolved transcriptome analysis." Doctoral thesis, Stockholms universitet, Institutionen för biokemi och biofysik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-110057.
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It is well known that cells in tissues display a large heterogeneity in gene expression due to differences in cell lineage origin and variation in the local environment at different sites in the tissue, a heterogeneity that is difficult to study by analyzing bulk RNA extracts from tissue. Recently, genome-wide transcriptome analysis technologies have enabled the analysis of this variation with single-cell resolution. In order to link the heterogeneity observed at molecular level with the morphological context of tissues, new methods are needed which achieve an additional level of information, such as spatial resolution. In this thesis I describe the development and application of padlock probes and rolling circle amplification (RCA) as molecular tools for spatially-resolved transcriptome analysis. Padlock probes allow in situ detection of individual mRNA molecules with single nucleotide resolution, visualizing the molecular information directly in the cell and tissue context. Detection of clinically relevant point mutations in tumor samples is achieved by using padlock probes in situ, allowing visualization of intra-tumor heterogeneity. To resolve more complex gene expression patterns, we developed in situ sequencing of RCA products combining padlock probes and next-generation sequencing methods. We demonstrated the use of this new method by, for the first time, sequencing short stretches of transcript molecules directly in cells and tissue. By using in situ sequencing as read-out for multiplexed padlock probe assays, we measured the expression of tens of genes in hundreds of thousands of cells, including point mutations, fusions transcripts and gene expression level. These molecular tools can complement genome-wide transcriptome analyses adding spatial resolution to the molecular information. This level of resolution is important for the understanding of many biological processes and potentially relevant for the clinical management of cancer patients.At the time of the doctoral defense, the following paper was unpublished and had a status as follows: Paper 4: Manuscript.
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Vickovic, Sanja. "Transcriptome-wide analysis in cells and tissues." Doctoral thesis, KTH, Genteknologi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-199447.
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High-throughput sequencing has greatly influenced the amount of data produced and biological questions asked and answered. Sequencing approaches have also enabled rapid development of related technological fields such as single-cell and spatially resolved expression profiling. The introductory parts of this thesis give an overview of the basic molecular and technological apparatus needed to analyse the transcriptome in cells and tissues. This is succeeded by a summary of present investigations that report recent advancements in RNA profiling. RNA integrity needs to be preserved for accurate gene expression analysis. A method providing a low-cost alternative for RNA preservation was reported. Namely, a low concentration of buffered formaldehyde was used for fixation of human cell lines and peripheral blood cells (Paper I). The results from bulk RNA sequencing confirmed gene expression was not negatively impacted with the preservation procedure (r2>0.88) and that long-term storage of such samples was possible (r2=0.95). However, it is important to note that a small population of cells overexpressing a limited amount of genes can skew bulk gene expression analyses making them sufficient only in carefully designed studies. Therefore, gene expression should be investigated at the single cell resolution when possible. A method for high-throughput single cell expression profiling termed microarrayed single-cell sequencing was developed (Paper II). The method incorporated fluorescence-activated cell sorting, sample deposition and profiling of thousands of barcoded single cells in one reaction. After sample attachment to a barcoded array, a high-resolution image was taken which linked the position of each array barcode sequence to each individual deposited cell. The cDNA synthesis efficiency was estimated at 17.3% while detecting 27,427 transcripts per cell on average. Additionally, spatially resolved analysis is important in cell differentiation, organ development and pathological changes. Current methods are limited in terms of throughput, cost and time. For that reason, the spatial transcriptomics method was developed (Paper III). Here, the barcoded microarray was used to obtain spatially resolved expression profiles from tissue sections using the same imaging principle. The mouse olfactory bulb was profiled on a whole-transcriptome scale and the results showed that the expression correlated well (r2=0.94-0.97) as compared to bulk RNA sequencing. The method was 6.9% efficient, reported signal diffusion at ~2 μm and accurately deconvoluted layer-specific transcripts in an unbiased manner. Lastly, the spatial transcriptomics concept was applied to profile human breast tumours in three dimensions (Paper IV). Unbiased clustering revealed previously un-annotated regions and classified them as parts of the immune system, providing a detailed view into complex interactions and crosstalk in the whole tissue volume. Spatial tumour classification divulged that certain parts of the tumour clearly classified as other subtypes as compared to bulk analysis providing useful data for current practice diagnostics. The last part of the thesis discusses a look towards the future, how the presented methods could be used, improved upon or combined in translational research.QC 20170109
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Zhang, Yang. "A visualization interface for spatial pathway regulation data." Thesis, KTH, Skolan för kemi, bioteknologi och hälsa (CBH), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-237741.
Full textAbstract:
Data visualization is an essential methodology for bioinformatics studies. Spatial Transcriptomics(ST) is a method that aims at measuring the transcriptome of tissue sections while maintaining its spacial information. Finally, the study of biological pathway focuses on a series of biochemical reactions that take place in organisms. As these studies generate a large number of datasets, this thesis attempts to combine the ST’s data with pathwayinformation and visualize it in an intuitive way to assist user comprehension and insight.In this thesis, Python was used for integrating the dataset and JavaScript libraries wereused for building the visualization. The processing of ST pathway data together with the data visualization interface are the outcomes of this thesis. The data visualization can show the regulation of pathways in the ST data and can be accessed by modern browsers. These outcomes can help users navigate the ST and pathway datasets more effectively.Datavisualisering är en viktig del av bioinformatik. Spatial transkriptomik (ST) är en metod som mäter transkriptom, samtidigt som den behåller spatial information. Biologiskapathways å andrasidan fokuserar på biokemiska reaktioner som sker inom organismer. Dessa studier genererar mycket data, och denna avhandling försöker att kombinera ST-data med pathway information och få en intuitiv visualisering av det integrerade datat.I avhandlingen användes Python för att integrera datat och JavaScript bibliotek för attbygga visualiseringsverktyget. Avhandlingen resulterade i en metod för att integrera STdata och pathway information, samt ett visualiseringsverktyg för ovan nämnda information.Verktyget kan visa pathway regulationer i ST data och kan användas i moderna webbläsare.Forskningen resulterade i ett verktyg som kan hjälpa forskare att förstå ST och pathwaydata.
Books on the topic "Spatial transcriptomic"
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Madan, Esha. Cutting Edge Artificial Intelligence, Spatial Transcriptomics and Proteomics Approaches to Analyze Cancer. Elsevier Science & Technology Books, 2024.
Find full textBook chapters on the topic "Spatial transcriptomic"
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Zhu, Qian. "A Hidden Markov Random Field Model for Detecting Domain Organizations from Spatial Transcriptomic Data." In Methods in Molecular Biology, 251–68. New York, NY: Springer New York, 2019. http://dx.doi.org/10.1007/978-1-4939-9057-3_16.
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Nichterwitz, Susanne, Julio Aguila Benitez, Rein Hoogstraaten, Qiaolin Deng, and Eva Hedlund. "LCM-Seq: A Method for Spatial Transcriptomic Profiling Using Laser Capture Microdissection Coupled with PolyA-Based RNA Sequencing." In Methods in Molecular Biology, 95–110. New York, NY: Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4939-7213-5_6.
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Achim, Kaia, Hernando Martínez Vergara, and Jean-Baptiste Pettit. "Spatial Transcriptomics: Constructing a Single-Cell Resolution Transcriptome-Wide Expression Atlas." In Methods in Molecular Biology, 111–25. New York, NY: Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4939-7213-5_7.
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Raghubar, Arti M., Joanna Crawford, Kahli Jones, Pui Y. Lam, Stacey B. Andersen, Nicholas A. Matigian, Monica S. Y. Ng, Helen Healy, Andrew J. Kassianos, and Andrew J. Mallett. "Spatial Transcriptomics in Kidney Tissue." In Methods in Molecular Biology, 233–82. New York, NY: Springer US, 2023. http://dx.doi.org/10.1007/978-1-0716-3179-9_17.
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Sammeth, Michael, Susann Mudra, Sina Bialdiga, Beate Hartmannsberger, Sofia Kramer, and Heike Rittner. "Comparative Methods for Demystifying Spatial Transcriptomics." In Comparative Genomics, 515–46. New York, NY: Springer US, 2024. http://dx.doi.org/10.1007/978-1-0716-3838-5_17.
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Charitakis, Natalie, Mirana Ramialison, and Hieu T. Nim. "Comparative Analysis of Packages and Algorithms for the Analysis of Spatially Resolved Transcriptomics Data." In Transcriptomics in Health and Disease, 165–86. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-87821-4_7.
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Ma, Cong, Uthsav Chitra, Shirley Zhang, and Benjamin J. Raphael. "Belayer: Modeling Discrete and Continuous Spatial Variation in Gene Expression from Spatially Resolved Transcriptomics." In Lecture Notes in Computer Science, 372–73. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-04749-7_33.
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Rao, Bovey Y., Alexis M. Peterson, Elena K. Kandror, Stephanie Herrlinger, Attila Losonczy, Liam Paninski, Abbas H. Rizvi, and Erdem Varol. "Non-parametric Vignetting Correction for Sparse Spatial Transcriptomics Images." In Medical Image Computing and Computer Assisted Intervention – MICCAI 2021, 466–75. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-87237-3_45.
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Xue, Shuailin, Fangfang Zhu, Changmiao Wang, and Wenwen Min. "stEnTrans: Transformer-Based Deep Learning for Spatial Transcriptomics Enhancement." In Bioinformatics Research and Applications, 63–75. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-5128-0_6.
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Fang, Donghai, Yichen Gao, Zhaoying Wang, Fangfang Zhu, and Wenwen Min. "Contrastive Masked Graph Autoencoders for Spatial Transcriptomics Data Analysis." In Bioinformatics Research and Applications, 76–88. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-5128-0_7.
Full textConference papers on the topic "Spatial transcriptomic"
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Smiljković, Lazar, Marko Mišić, Predrag Obradović, and Vladimir Kovačević. "Incorporating Practical Single Cell and Spatial Transcriptomics Analysis in a Bioinformatics Course." In 2024 11th International Conference on Electrical, Electronic and Computing Engineering (IcETRAN), 1–6. IEEE, 2024. http://dx.doi.org/10.1109/icetran62308.2024.10645128.
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Li, Guangyuan (Frank), Amir Bayegan, Joon Sang Lee, Donald Jackson, and Jack Pollard. "926 Evaluating diverse deconvolution methods for tumor spatial transcriptomic datasets." In SITC 37th Annual Meeting (SITC 2022) Abstracts. BMJ Publishing Group Ltd, 2022. http://dx.doi.org/10.1136/jitc-2022-sitc2022.0926.
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Danaher, Patrick, Emily Killingbeck, Yan Liang, Megan Vandenberg, Sarah Church, Joseph Beechem, and Sangsoon Woo. "156 Spatial transcriptomic signatures of the fundamentals of immuno-oncology." In SITC 38th Annual Meeting (SITC 2023) Abstracts. BMJ Publishing Group Ltd, 2023. http://dx.doi.org/10.1136/jitc-2023-sitc2023.0156.
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KUNCHEVA, ZHANA, MICHELLE L. KRISHNAN, and GIOVANNI MONTANA. "EXPLORING BRAIN TRANSCRIPTOMIC PATTERNS: A TOPOLOGICAL ANALYSIS USING SPATIAL EXPRESSION NETWORKS." In Proceedings of the Pacific Symposium. WORLD SCIENTIFIC, 2016. http://dx.doi.org/10.1142/9789813207813_0008.
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Schachter, Michael, Lu Sun, Wesley Kwong, Samantha Liang, Sandra Santulli-Marotto, Lacey Kitch, Willy Hugo, Robert Prins, and Dinesh Kumar. "643 Spatial-transcriptomic analysis of neoadjuvant checkpoint immunotherapy in recurrent glioblastoma." In SITC 37th Annual Meeting (SITC 2022) Abstracts. BMJ Publishing Group Ltd, 2022. http://dx.doi.org/10.1136/jitc-2022-sitc2022.0643.
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Park, Wungki, Fergus Keane, Hulya Sahin Ozkan, Allison Richards, Vasilisa Rudneva, Danny Khalil, Kevin Soares, et al. "115 Comprehensive spatial, transcriptomic, and genomic analysis of immunogenic biliary tract cancer." In SITC 38th Annual Meeting (SITC 2023) Abstracts. BMJ Publishing Group Ltd, 2023. http://dx.doi.org/10.1136/jitc-2023-sitc2023.0115.
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Joulia, R., W. Traves, F. Puttur, L. Yates, S. Siddiqui, S. Saglani, and C. Lloyd. "Investigation into the lung vasculature transcriptional signature during asthma using spatial transcriptomic." In ERS Lung Science Conference 2024 abstracts. European Respiratory Society, 2024. http://dx.doi.org/10.1183/23120541.lsc-2024.54.
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Stott, Ryan, Jawad Abousoud, Stephen Williams, Shamoni Maheshwari, Valeria Giangarra, Sarah Taylor, and Andrew Kohlway. "174 Single cell FFPE and spatial transcriptomic profiling of an invasive ductal carcinoma enhances cellular and spatial insights." In SITC 37th Annual Meeting (SITC 2022) Abstracts. BMJ Publishing Group Ltd, 2022. http://dx.doi.org/10.1136/jitc-2022-sitc2022.0174.
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Michelle, Naughton, Kee Rachael, McDonnell Gavin V, Howell Owain W, and Fitzgerald Denise C. "Transcriptomic spatial analysis and multiplex RNAscope of meningeal and perivascular inflammation in multiple sclerosis." In Association of British Neurologists: Annual Meeting Abstracts 2023. BMJ Publishing Group Ltd, 2023. http://dx.doi.org/10.1136/jnnp-2023-abn.21.
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Justet, A., T. Adams, A. Balayev, T. Baernthaler, F. Poli, J. D. Cala Garcia, J. E. Mcdonough, et al. "Spatial Transcriptomic Analysis Allow the Identification of Abnormal Airway Niches in the Fibrotic Lung." In American Thoracic Society 2023 International Conference, May 19-24, 2023 - Washington, DC. American Thoracic Society, 2023. http://dx.doi.org/10.1164/ajrccm-conference.2023.207.1_meetingabstracts.a1033.
Full textReports on the topic "Spatial transcriptomic"
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Brown Horowitz, Sigal, Eric L. Davis, and Axel Elling. Dissecting interactions between root-knot nematode effectors and lipid signaling involved in plant defense. United States Department of Agriculture, January 2014. http://dx.doi.org/10.32747/2014.7598167.bard.
Full textAbstract:
Root-knot nematodes, Meloidogynespp., are extremely destructive pathogens with a cosmopolitan distribution and a host range that affects most crops. Safety and environmental concerns related to the toxicity of nematicides along with a lack of natural resistance sources threaten most crops in Israel and the U.S. This emphasizes the need to identify genes and signal mechanisms that could provide novel nematode control tactics and resistance breeding targets. The sedentary root-knot nematode (RKN) Meloidogynespp. secrete effectors in a spatial and temporal manner to interfere with and mimic multiple physiological and morphological mechanisms, leading to modifications and reprogramming of the host cells' functions, resulted in construction and maintenance of nematodes' feeding sites. For successful parasitism, many effectors act as immunomodulators, aimed to manipulate and suppress immune defense signaling triggered upon nematode invasion. Plant development and defense rely mainly on hormone regulation. Herein, a metabolomic profiling of oxylipins and hormones composition of tomato roots were performed using LC-MS/MS, indicating a fluctuation in oxylipins profile in a compatible interaction. Moreover, further attention was given to uncover the implication of WRKYs transcription factors in regulating nematode development. In addition, in order to identify genes that might interact with the lipidomic defense pathway induced by oxylipins, a RNAseq was performed by exposing M. javanicasecond-stage juveniles to tomato protoplast, 9-HOT and 13-KOD oxylipins. This transcriptome generated a total of 4682 differentially expressed genes (DEGs). Being interested in effectors, we seek for DEGs carrying a predicted secretion signal peptide. Among the DEGs including signal peptide, several had homology with known effectors in other nematode species, other unknown potentially secreted proteins may have a role as root-knot nematodes' effectors which might interact with lipid signaling. The molecular interaction of LOX proteins with the Cyst nematode effectors illustrate the nematode strategy in manipulating plant lipid signals. The function of several other effectors in manipulating plant defense signals, as well as lipids signals, weakening cell walls, attenuating feeding site function and development are still being studied in depth for several novel effectors. As direct outcome of this project, the accumulating findings will be utilized to improve our understanding of the mechanisms governing critical life-cycle phases of the parasitic M. incognita RKN, thereby facilitating design of effective controls based on perturbation of nematode behavior—without producing harmful side effects. The knowledge from this study will promote genome editing strategies aimed at developing nematode resistance in tomato and other nematode-susceptible crop species in Israel and the United States.