scholarly journals Transcriptome Analysis of the Gene Expression Profiles Associated with Fungal Keratitis in Mice Based on RNA-Seq

2020 ◽  
Vol 61 (6) ◽  
pp. 32
Author(s):  
Qing Zhang ◽  
Jian Zhang ◽  
Mengting Gong ◽  
Ruolan Pan ◽  
Yanchang Liu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcriptome Analysis ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Fungal Keratitis ◽  
Rna Seq

scholarly journals Transcriptome analysis of gravitational effects on mouse skeletal muscles under microgravity and artificial 1 g onboard environment

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Risa Okada ◽  
Shin-ichiro Fujita ◽  
Riku Suzuki ◽  
Takuto Hayashi ◽  
Hirona Tsubouchi ◽  
...  
Keyword(s):  
Gene Expression ◽  
Muscle Mass ◽  
Muscle Atrophy ◽  
Transcriptome Analysis ◽  
Fiber Type ◽  
Expression Profiles ◽  
Space Station ◽  
Gene Expression Profiles

AbstractSpaceflight causes a decrease in skeletal muscle mass and strength. We set two murine experimental groups in orbit for 35 days aboard the International Space Station, under artificial earth-gravity (artificial 1 g; AG) and microgravity (μg; MG), to investigate whether artificial 1 g exposure prevents muscle atrophy at the molecular level. Our main findings indicated that AG onboard environment prevented changes under microgravity in soleus muscle not only in muscle mass and fiber type composition but also in the alteration of gene expression profiles. In particular, transcriptome analysis suggested that AG condition could prevent the alterations of some atrophy-related genes. We further screened novel candidate genes to reveal the muscle atrophy mechanism from these gene expression profiles. We suggest the potential role of Cacng1 in the atrophy of myotubes using in vitro and in vivo gene transductions. This critical project may accelerate the elucidation of muscle atrophy mechanisms.

scholarly journals A tensor decomposition-based integrated analysis applicable to multiple gene expression profiles without sample matching

2021 ◽  
Author(s):  
Taguchi Y-h. ◽  
Turki Turki
Keyword(s):  
Gene Expression ◽  
Learning Strategies ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Tensor Decomposition ◽  
Integrated Analysis ◽  
Rna Seq ◽  
Prior Learning ◽  
Multiple Gene ◽  
Machine Learning Applications

Abstract The integrated analysis of multiple gene expression profiles measured in distinct studies is always problematic. Especially, missing sample matching and missing common labeling between distinct studies prevent the integration of multiple studies in fully data-driven and unsupervised manner. In this study, we propose a strategy enabling the integration of multiple gene expression profiles among multiple independent studies without either labeling or sample matching, using tensor decomposition-based unsupervised feature extraction. As an example, we applied this strategy to Alzheimer’s disease (AD)-related gene expression profiles that lack exact correspondence among samples as well as AD single-cell RNA-seq (scRNA-seq) data. We found that we could select biologically reasonable genes with integrated analysis. Overall, integrated gene expression profiles can function analogously to prior learning and/or transfer learning strategies in other machine learning applications. For scRNA-seq, the proposed approach was able to drastically reduce the required computational memory.

scholarly journals High resolution spatial transcriptome analysis by photo-isolation chemistry

2020 ◽  
Author(s):  
Mizuki Honda ◽  
Shinya Oki ◽  
Akihito Harada ◽  
Kazumitsu Maehara ◽  
Kaori Tanaka ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcriptome Analysis ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Transcriptome Profiling ◽  
Tissue Sections ◽  
Complex Functions ◽  
Multicellular Organisms

ABSTRACTIn multicellular organisms, individual cells are characterized by their gene expression profiles and the spatial interactions among cells enable the elaboration of complex functions. Expression profiling in spatially defined regions is crucial to elucidate cell interactions and functions. Here, we established a transcriptome profiling method coupled with photo-isolation chemistry (PIC) that allows the determination of expression profiles specifically from photo-irradiated regions of whole tissues. PIC uses photo-caged oligodeoxynucleotides for in situ reverse transcription. After photo-irradiation of limited areas, gene expression was detected from at least 10 cells in the tissue sections. PIC transcriptome analysis detected genes specifically expressed in small distinct areas of the mouse embryo. Thus, PIC enables transcriptome profiles to be determined from limited regions at a spatial resolution up to the diffraction limit.

The characteristics of mesenteric adipose tissue attached to different intestinal segments and their roles in immune regulation

2022 ◽  
Author(s):  
Haowei Zhang ◽  
Yujin Ding ◽  
Qin Zeng ◽  
Dandan Wang ◽  
Ganglei Liu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Adipose Tissue ◽  
Immune Regulation ◽  
Expression Profiles ◽  
Critical Role ◽  
Gene Expression Profiles ◽  
Rna Seq ◽  
Mesenteric Adipose Tissue ◽  
Cell Components ◽  
Subsequent Effect

Background: Mesenteric adipose tissue (MAT) plays a critical role in the intestinal physiological ecosystems. Small and large intestines have evidently intrinsic and distinct characteristics. However, whether there exist any mesenteric differences adjacent to the small and large intestines (SMAT and LMAT) has not been properly characterized. We studied the important facets of these differences, such as morphology, gene expression, cell components and immune regulation of MATs, to characterize the mesenteric differences. Methods: The SMAT and LMAT of mice were utilized for comparison of tissue morphology. Paired mesenteric samples were analyzed by RNA-seq to clarify gene expression profiles. MAT partial excision models were constructed to illustrate the immune regulation roles of MATs, and 16S-seq was applied to detect the subsequent effect on microbiota. Results: Our data show that different segments of mesenteries have different morphological structures. SMAT not only has smaller adipocytes but also contains more fat-associated lymphoid clusters than LMAT. The gene expression profile is also discrepant between these two MATs in mice. B-cell markers were abundantly expressed in SMAT, while development-related genes were highly expressed in LMAT. Adipose-derived stem cells of LMAT exhibited higher adipogenic potential and lower proliferation rates than those of SMAT. In addition, SMAT and LMAT play different roles in immune regulation and subsequently affect microbiota components. Finally, our data clarified the described differences between SMAT and LMAT in humans. Conclusions: There were significant differences in cell morphology, gene expression profiles, cell components, biological characteristics, and immune and microbiota regulation roles between regional MATs.

scholarly journals Comparative Transcriptome Analysis of Different Dendrobium Species Reveals Active Ingredients-Related Genes and Pathways

2020 ◽  
Vol 21 (3) ◽  
pp. 861 ◽  
Author(s):  
Yingdan Yuan ◽  
Bo Zhang ◽  
Xinggang Tang ◽  
Jinchi Zhang ◽  
Jie Lin
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Rna Seq ◽  
Active Ingredients ◽  
Hub Genes ◽  
Transcriptome Database ◽  
Gene Modules ◽  
Functional Investigation ◽  
First Time

Dendrobium is widely used in traditional Chinese medicine, which contains many kinds of active ingredients. In recent years, many Dendrobium transcriptomes have been sequenced. Hence, weighted gene co-expression network analysis (WGCNA) was used with the gene expression profiles of active ingredients to identify the modules and genes that may associate with particular species and tissues. Three kinds of Dendrobium species and three tissues were sampled for RNA-seq to generate a high-quality, full-length transcriptome database. Based on significant changes in gene expression, we constructed co-expression networks and revealed 19 gene modules. Among them, four modules with properties correlating to active ingredients regulation and biosynthesis, and several hub genes were selected for further functional investigation. This is the first time the WGCNA method has been used to analyze Dendrobium transcriptome data. Further excavation of the gene module information will help us to further study the role and significance of key genes, key signaling pathways, and regulatory mechanisms between genes on the occurrence and development of medicinal components of Dendrobium.

scholarly journals Distinct Gene Expression Profiles of Viral- and Nonviral-Associated Merkel Cell Carcinoma Revealed by Transcriptome Analysis

2013 ◽  
Vol 133 (4) ◽  
pp. 936-945 ◽  
Author(s):  
Paul W. Harms ◽  
Rajiv M. Patel ◽  
Monique E. Verhaegen ◽  
Thomas J. Giordano ◽  
Kevin T. Nash ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Carcinoma ◽  
Merkel Cell Carcinoma ◽  
Transcriptome Analysis ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Merkel Cell ◽  
Distinct Gene
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