scholarly journals High expression of VRT2 during wheat spikelet initiation increases the number of rudimentary basal spikelets

2021 ◽  
Author(s):  
Anna E Backhaus ◽  
Ashleigh Lister ◽  
Melissa Tomkins ◽  
Nikolai M. Adamski ◽  
James Simmonds ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Computational Modelling ◽  
Gene Expression Profiles ◽  
Building Blocks ◽  
Field Trials ◽  
Developmental Genetics ◽  
Spatially Resolved ◽  
Before And After ◽  
Single Spike

Spikelets are the fundamental building blocks of Poaceae inflorescences and their development and branching patterns determine the various inflorescence architectures and grain yield of grasses. In wheat, the central spikelets produce the most and largest grains, while spikelet size gradually decreases acro- and basipetally, giving rise to the characteristic lanceolate shape of wheat spikes. The acropetal gradient correlates with the developmental age of spikelets, however the basal spikelets are developed first and the cause of their small size and rudimentary development is unclear. Here, we adapted G&T-seq, a low-input transcriptomics approach, to characterise gene expression profiles within spatial sections of individual spikes before and after the establishment of the lanceolate shape. We observed larger differences in gene expression profiles between the apical, central and basal sections of a single spike than between any section belonging to consecutive developmental timepoints. We found that SVP MADS-box transcription factors, including VRT-A2, are expressed highest in the basal section of the wheat spike and display the opposite expression gradient to flowering E-class SEP1 genes. Based on multi-year field trials and transgenic lines we show that higher expression of VRT-A2 in the basal sections of the spike is associated with increased numbers of rudimentary basal spikelets. Our results, supported by computational modelling, suggest that the delayed transition of basal spikelets from vegetative to floral developmental programmes results in the lanceolate shape of wheat spikes. This study highlights the value of spatially resolved transcriptomics to gain new insights into developmental genetics pathways of grass inflorescences.

Assessment of cancer prevention effect of exercise

2021 ◽  
pp. 1-6
Author(s):  
Reza Vafaee ◽  
Mostafa Rezaei Tavirani ◽  
Sina Rezaei Tavirani ◽  
Mohammadreza Razzaghi
Keyword(s):  
Gene Expression ◽  
Cancer Prevention ◽  
Human Health ◽  
Expression Profiles ◽  
Vastus Lateralis ◽  
Gene Expression Profiles ◽  
Gene Expression Omnibus ◽  
Vastus Lateralis Muscle ◽  
Before And After ◽  
Exercise Training Intervention

There are many documents about benefits of exercise on human health. However, evidences indicate to positive effect of exercise on disease prevention, understanding of many aspects of this mechanism need more investigations. Determination of critical genes which effect human health. GSE156249 including 12 gene expression profiles of healthy individual biopsy from vastus lateralis muscle before and after 12-week combined exercise training intervention were extracted from gene expression omnibus (GEO) database. The significant DEGs were included in interactome unit by Cytoscape software and STRING database. The network was analyzed to find the central nodes subnetwork clusters. The nodes of prominent cluster were assessed via gene ontology by using ClueGO. Number of 8 significant DEGs and 100 first neighbors analyzed via network analysis. The network includes 2 clusters and COL3A1, BGN, and LOX were determined as central DEGs. The critical DEGs were involved in cancer prevention process.

scholarly journals Biological Insights into Chemotherapy Resistance in Ovarian Cancer

2019 ◽  
Vol 20 (9) ◽  
pp. 2131 ◽  
Author(s):  
Michelle A. Glasgow ◽  
Peter Argenta ◽  
Juan E. Abrahante ◽  
Mihir Shetty ◽  
Shobhana Talukdar ◽  
...  
Keyword(s):  
Gene Expression ◽  
Ovarian Cancer ◽  
Expression Profiles ◽  
Rna Extraction ◽  
Chemotherapy Resistance ◽  
Gene Expression Profiles ◽  
Gene Set Enrichment Analysis ◽  
Before And After ◽  
Tumor Gene Expression ◽  
Tumor Gene

The majority of patients with high-grade serous ovarian cancer (HGSOC) initially respond to chemotherapy; however, most will develop chemotherapy resistance. Gene signatures may change with the development of chemotherapy resistance in this population, which is important as it may lead to tailored therapies. The objective of this study was to compare tumor gene expression profiles in patients before and after treatment with neoadjuvant chemotherapy (NACT). Tumor samples were collected from six patients diagnosed with HGSOC before and after administration of NACT. RNA extraction and whole transcriptome sequencing was performed. Differential gene expression, hierarchical clustering, gene set enrichment analysis, and pathway analysis were examined in all of the samples. Tumor samples clustered based on exposure to chemotherapy as opposed to patient source. Pre-NACT samples were enriched for multiple pathways involving cell cycle growth. Post-NACT samples were enriched for drug transport and peroxisome pathways. Molecular subtypes based on the pre-NACT sample (differentiated, mesenchymal, proliferative and immunoreactive) changed in four patients after administration of NACT. Multiple changes in tumor gene expression profiles after exposure to NACT were identified from this pilot study and warrant further attention as they may indicate early changes in the development of chemotherapy resistance.

scholarly journals Signature pathways identified from gene expression profiles in the human uterine cervix before and after spontaneous term parturition

2007 ◽  
Vol 197 (3) ◽  
pp. 250.e1-250.e7 ◽  
Author(s):  
Sonia S. Hassan ◽  
Roberto Romero ◽  
Adi L. Tarca ◽  
Sorin Draghici ◽  
Beth Pineles ◽  
...  
Keyword(s):  
Gene Expression ◽  
Uterine Cervix ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Before And After

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.

Analysis of the Effect On the Expression of Global Gene Expression Profiles in Lymphocyte Subpopulations Treated by Extracorporeal Photopheresis

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 4841-4841
Author(s):  
Robert M Knobler ◽  
Ulrike Just ◽  
Gabriele Klosner ◽  
Florian Klinglmueller ◽  
Martin Bilban ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lymphocyte Subsets ◽  
Expression Profiles ◽  
Chronic Gvhd ◽  
Gene Expression Profiles ◽  
Global Gene Expression ◽  
Extracorporeal Photopheresis ◽  
Cd4 Cells ◽  
Before And After

Abstract Abstract 4841 Introduction After the initial introduction of extracorporeal photopheresis (ECP) for the therapy of Sezary syndrome (CTCL) it has been found to have significant clinical effect on other T-cell mediated diseases including graft-versus-host disease (GvHD), organ transplant rejection, systemic sclerosis and other autoimmune disorders. To obtain information about modifications in gene expression patterns before and after ECP and to define gene sets with important changes in expression we analysed gene expression profiles in major lymphocyte subsets of patients before and after treatment with 8-methoxypsoralen (8-MOP) and ultraviolet A (UVA) irradiation. Patients, Materials, and Methods For this initial study 6 female patients suffering from chronic GvHD under treatment with ECP were included. Affymetrix® Human Genome U133 Plus 2.0 Arrays were used to compare global gene expression profiles in CD4+ and CD8+ lymphocytes before and after ECP. Lymphocyte subsets were isolated before and immediately after exposure to 8-MOP/UVA during a standard ECP treatment cycle. Total RNA was isolated from each cell sample and processed and analyzed according to standard procedures. Results Preliminary data suggest a significant effect in CD4+ and CD8+ lymphocytes in patients with chronic GvHD on gene transcription after 8-MOP/UVA exposure. In CD4+ cells 20 times more gene transcription can be detected when compared to CD8+ cells. These findings underline the possible key role of CD4+ cells in the mechanisms of action of ECP. Recent research in animal models found evidence for a role of CD4+ regulatory T cells in the immunomodulatory activity of ECP. Conclusion The scientific approach of this study has the advantage of exploring global gene regulatory effects of ECP without any experimental bias based on earlier evidence or on a mechanistic hypothesis. Its results offer the advantage of finding new and so far unexplored effects of ECP on the treated cells; information which should be able to generate significant data to help define key targets for subsequent research into the mechanism of action of ECP. Disclosures: No relevant conflicts of interest to declare.

scholarly journals Meta-Analysis of Hypoxic Transcriptomes from Public Databases

Biomedicines ◽  
2020 ◽  
Vol 8 (1) ◽  
pp. 10 ◽  
Author(s):  
Hidemasa Bono ◽  
Kiichi Hirota
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Meta Analysis ◽  
Gene Expression Profiles ◽  
Data Driven ◽  
Transcriptome Data ◽  
Rna Seq ◽  
Experimental Conditions ◽  
Oxygen Homeostasis ◽  
Before And After

Hypoxia is the insufficiency of oxygen in the cell, and hypoxia-inducible factors (HIFs) are central regulators of oxygen homeostasis. In order to obtain functional insights into the hypoxic response in a data-driven way, we attempted a meta-analysis of the RNA-seq data from the hypoxic transcriptomes archived in public databases. In view of methodological variability of archived data in the databases, we first manually curated RNA-seq data from appropriate pairs of transcriptomes before and after hypoxic stress. These included 128 human and 52 murine transcriptome pairs. We classified the results of experiments for each gene into three categories: upregulated, downregulated, and unchanged. Hypoxic transcriptomes were then compared between humans and mice to identify common hypoxia-responsive genes. In addition, meta-analyzed hypoxic transcriptome data were integrated with public ChIP-seq data on the known human HIFs, HIF-1 and HIF-2, to provide insights into hypoxia-responsive pathways involving direct transcription factor binding. This study provides a useful resource for hypoxia research. It also demonstrates the potential of a meta-analysis approach to public gene expression databases for selecting candidate genes from gene expression profiles generated under various experimental conditions.

Gene expression profiles from hypertrophic scar fibroblasts before and after IL-6 stimulation

2004 ◽  
Vol 202 (4) ◽  
pp. 476-485 ◽  
Author(s):  
Mohan RK Dasu ◽  
Hal K Hawkins ◽  
Robert E Barrow ◽  
Hui Xue ◽  
David N Herndon
Keyword(s):  
Gene Expression ◽  
Hypertrophic Scar ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Before And After

scholarly journals Missing-value imputation and in silico region detection for spatially resolved transcriptomics

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

We are pleased to introduce a first–of–its–kind algorithm that combines in–silico region detection and spatial gene expression imputation. 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 individual tissue regions. 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 subtle intra–tissue heterogeneity and recover spatial gene–gene interaction signals. We therefore strongly encourage using MIST prior to downstream ST analysis because it provides unbiased region annotations and enables accurately de–noised spatial gene expression profiles.

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