scholarly journals Systematic Spatial Analysis of Gene Expression during Wheat Caryopsis Development

2005 ◽  
Vol 17 (8) ◽  
pp. 2172-2185 ◽  
Author(s):  
Sinéad Drea ◽  
David J. Leader ◽  
Ben C. Arnold ◽  
Peter Shaw ◽  
Liam Dolan ◽  
...  
Keyword(s):  
Gene Expression ◽  
Spatial Analysis

scholarly journals Spatial Analysis of Single Fiber Cells of the Developing Ocular Lens Reveals Regulated Heterogeneity of Gene Expression

2018 ◽  
Author(s):  
Rajendra K. Gangalum ◽  
Dongjae Kim ◽  
Raj K. Kashyap ◽  
Serghei Mangul ◽  
Xinkai Zhou ◽  
...  
Keyword(s):  
Gene Expression ◽  
Spatial Analysis ◽  
Single Fiber ◽  
Ocular Lens ◽  
Fiber Cells

scholarly journals Spatial Analysis of Single Fiber Cells of the Developing Ocular Lens Reveals Regulated Heterogeneity of Gene Expression

iScience ◽  
2018 ◽  
Vol 10 ◽  
pp. 66-79 ◽  
Author(s):  
Rajendra K. Gangalum ◽  
Dongjae Kim ◽  
Raj K. Kashyap ◽  
Serghei Mangul ◽  
Xinkai Zhou ◽  
...  
Keyword(s):  
Gene Expression ◽  
Spatial Analysis ◽  
Single Fiber ◽  
Ocular Lens ◽  
Fiber Cells

scholarly journals Spatial Analysis of Arabidopsis thaliana Gene Expression in Response to Turnip mosaic virus Infection

2007 ◽  
Vol 20 (4) ◽  
pp. 358-370 ◽  
Author(s):  
Chunling Yang ◽  
Rong Guo ◽  
Fei Jie ◽  
Dan Nettleton ◽  
Jiqing Peng ◽  
...  
Keyword(s):  
Gene Expression ◽  
Arabidopsis Thaliana ◽  
Spatial Analysis ◽  
Mosaic Virus ◽  
Expression Profiles ◽  
Turnip Mosaic Virus ◽  
Infected Leaf ◽  
Altered Expression ◽  
Virus Accumulation ◽  
Mrna Transcripts

Virus-infected leaf tissues comprise a heterogeneous mixture of cells at different stages of infection. The spatial and temporal relationships between sites of virus accumulation and the accompanying host responses, such as altered host gene expression, are not well defined. To address this issue, we utilized Turnip mosaic virus (TuMV) tagged with the green fluorescent protein to guide the dissection of infection foci into four distinct zones. The abundance of Arabidopsis thaliana mRNA transcripts in each of the four zones then was assayed using the Arabidopsis ATH1 GeneChip oligonucleotide microarray (Affymetrix). mRNA transcripts with significantly altered expression profiles were determined across gradients of virus accumulation spanning groups of cells in and around foci at different stages of infection. The extent to which TuMV-responsive genes were up- or downregulated primarily correlated with the amount of virus accumulation regardless of gene function. The spatial analysis also allowed new suites of coordinately regulated genes to be identified that are associated with chloroplast functions (decreased), sulfate assimilation (decreased), cell wall extensibility (decreased), and protein synthesis and turnover (induced). The functions of these downregulated genes are consistent with viral symptoms, such as chlorosis and stunted growth, providing new insight into mechanisms of pathogenesis.

scholarly journals Spatial analysis of biomineralization associated gene expression from the mantle organ of the pearl oyster Pinctada maxima

BMC Genomics ◽  
2011 ◽  
Vol 12 (1) ◽  
Author(s):  
Luke D Gardner ◽  
David Mills ◽  
Aaron Wiegand ◽  
David Leavesley ◽  
Abigail Elizur
Keyword(s):  
Gene Expression ◽  
Spatial Analysis ◽  
Pearl Oyster ◽  
Pinctada Maxima

Contributions of the spatial analysis of gene expression to the study of sea urchin development

1990 ◽  
pp. 69-96 ◽  
Author(s):  
Robert C. Angerer ◽  
Susan D. Reynolds ◽  
Julia Grimwade ◽  
David L. Hurley ◽  
Qing Yang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Spatial Analysis ◽  
Sea Urchin

Artificial intelligence-powered spatial analysis of tumor infiltrating lymphocytes (TIL) to reflect target gene expressions of novel immuno-oncology agents.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e14534-e14534
Author(s):  
Chan-Young Ock ◽  
Seunghwan Shin ◽  
Wonkyung Jung ◽  
Sangheon Ahn ◽  
Haejoon Kim ◽  
...  
Keyword(s):  
Gene Expression ◽  
Artificial Intelligence ◽  
Spatial Analysis ◽  
Rna Sequencing ◽  
Target Gene ◽  
Target Genes ◽  
Checkpoint Inhibitors ◽  
The Cancer Genome Atlas ◽  
Sequencing Data ◽  
Gene Expressions

e14534 Background: Novel immuno-oncology (IO) agents are promising but showing their efficacy in early phase clinical trials has been challenging due to limited enrichment strategies using practical biomarker platforms. We hypothesize that an artificial intelligence (AI)-powered spatial analysis of TIL using practically feasible H&E slides, can reflect a specific target gene expression derived from RNA sequencing. This enhances its potential application in early development of novel IO agents. Methods: An AI-powered spatial TIL analyzer, namely Lunit SCOPE IO, was developed with data from 2.8 x 109 micrometer2 H&E-stained tissue regions and 5.9 x 106 TILs from 3,166 whole slide images of multiple cancer types, annotated by board-certified pathologists. Inflamed Score and Immune-Excluded Score was defined as the proportion of all tumor-containing 1 mm2-size tiles within a WSI classified as being of inflamed immune phenotype (high TIL density within cancer epithelium) and immune-excluded phenotype (low TIL density within cancer epithelium, but high TIL density within stroma), respectively. We used RNA sequencing data and H&E images from The Cancer Genome Atlas database, excluding those of mesenchymal origin (n = 7,467). Spearman's rank correlation between each gene expression and IS or IES, respectively, was calculated. Correlation coefficient > 0.2 and false discovery rate (FDR) < 1% was considered as a significant correlation. Results: In a total of 20,304 genes, 871 (4.3%) and 1,155 (5.7%) genes were significantly correlated with Inflamed Score (IS) and Immune-Excluded Score (IES), respectively. The IS was highly related to genes reflecting immune cytolytic activity and targets of approved immune checkpoint inhibitors (Table). Interestingly, it was also significantly correlated with target genes of novel IO such as TIGIT, LAG3, TIM3, IDO, Adenosine receptor A2A, OX40, ICOS, M-CSF, IL2, IL7, and IL12. Moreover, the IES was exclusively correlated with the target genes of CEACAM, TGFB, and IL1. Conclusions: Expression levels of novel I-O target genes are correlated with three scores derived from AI-powered TIL analysis using H&E slides, which can be easily applied to clinical research.[Table: see text]

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