scholarly journals Transcriptional Differences between Canine Cutaneous Epitheliotropic Lymphoma and Immune-Mediated Dermatoses

Genes ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 160
Author(s):  
Nadja Gerber ◽  
Magdalena A. T. Brunner ◽  
Vidhya Jagannathan ◽  
Tosso Leeb ◽  
Nora M. Gerhards ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cell ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Principal Component ◽  
Diagnostic Biomarkers ◽  
Immune Mediated ◽  
Differential Gene ◽  
Skin Biopsies ◽  
Formalin Fixed

Canine cutaneous epitheliotropic T-cell lymphoma (CETL) and immune-mediated T-cell predominant dermatoses (IMD) share several clinical and histopathological features, but differ substantially in prognosis. The discrimination of ambiguous cases may be challenging, as diagnostic tests are limited and may prove equivocal. This study aimed to investigate transcriptional differences between CETL and IMD, as a basis for further research on discriminating diagnostic biomarkers. We performed 100bp single-end sequencing on RNA extracted from formalin-fixed and paraffin-embedded skin biopsies from dogs with CETL and IMD, respectively. DESeq2 was used for principal component analysis (PCA) and differential gene expression analysis. Genes with significantly different expression were analyzed for enriched pathways using two different tools. The expression of selected genes and their proteins was validated by RT-qPCR and immunohistochemistry. PCA demonstrated the distinct gene expression profiles of CETL and IMD. In total, 503 genes were upregulated, while 4986 were downregulated in CETL compared to IMD. RT-qPCR confirmed the sequencing results for 5/6 selected genes tested, while the protein expression detected by immunohistochemistry was not entirely consistent. Our study revealed transcriptional differences between canine CETL and IMD, with similarities to human cutaneous lymphoma. Differentially expressed genes are potential discriminatory markers, but require further validation on larger sample collections.

PSIV-6 Differential gene expression of fibro/adipogenic progenitors between Wagyu and Brahman cattle: A possible contribution to their different meat quality

2021 ◽  
Vol 99 (Supplement_3) ◽  
pp. 301-301
Author(s):  
Chaoyang Li ◽  
Qianglin Liu ◽  
Matt Welborn ◽  
Leshan Wang ◽  
Yuxia Li ◽  
...  
Keyword(s):  
Gene Expression ◽  
Skeletal Muscle ◽  
Meat Quality ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Cattle Breed ◽  
Intramuscular Fat ◽  
Brahman Cattle ◽  
Differential Gene ◽  
The Difference

Abstract The amount of intramuscular fat directly influences the meat quality. However, significant differences in the ability to accumulate intramuscular fat are present among different beef cattle breeds. While Wagyu, a cattle breed that originated from Japan, is renowned for abundant intramuscular fat, Brahman cattle generally have very little intramuscular fat accumulation and produce tougher meat. We identified that bovine intramuscular fat is derived from a group of bipotent progenitor cells named fibro/adipogenic progenitors (FAPs) which also give rise to fibroblasts. Thus, the variation in intramuscular fat development between Wagyu and Brahman is likely attributed to the difference in FAPs between these two breeds. In order to understand the gene expression difference between FAPs of the two breeds, single-cell RNA-seq was performed using total single-nucleated cells isolated from the longissimus muscle of young purebred Wagyu, purebred Brahman, and Wagyu-Brahman cross cattle. FAPs constitute the largest single-nucleated cell population in both Wagyu and Brahman skeletal muscle. Multiple subpopulations of FAPs with different gene expression profiles were identified, suggesting that FAP is a heterogeneous population. A unique FAP cluster expressing lower levels of fibrillar collagen and extracellular remodeling enzyme genes but higher levels of select proadipogenic genes was identified exclusively in Wagyu skeletal muscle, which likely contributes to the robust intramuscular adipogenic efficiency of Wagyu FAPs. In conclusion, the difference in the cellular composition and gene expression of FAPs between Wagyu and Brahman cattle likely contribute to their distinct meat quality.

scholarly journals Differential Gene Expression Profiles of Cells from Normal, Traumatic and Idiopathic Scoliotic Discs Identify Molecular Dysregulation in Scoliosis

2016 ◽  
Vol 6 (1_suppl) ◽  
pp. s-0036-1582635-s-0036-1582635 ◽  
Author(s):  
Sibylle Grad ◽  
Ying Zhang ◽  
Olga Rozhnova ◽  
Elena Schelkunova ◽  
Mikhail Mikhailovsky ◽  
...  
Keyword(s):  
Gene Expression ◽  
Differential Gene Expression ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Differential Gene

scholarly journals PCA-based unsupervised feature extraction for gene expression analysis of COVID-19 patients

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kota Fujisawa ◽  
Mamoru Shimo ◽  
Y.-H. Taguchi ◽  
Shinya Ikematsu ◽  
Ryota Miyata
Keyword(s):  
Gene Expression ◽  
Feature Extraction ◽  
Target Genes ◽  
Gene Selection ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Principal Component ◽  
Data Set ◽  
Immune Related Genes ◽  
Unsupervised Feature Extraction

AbstractCoronavirus disease 2019 (COVID-19) is raging worldwide. This potentially fatal infectious disease is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, the complete mechanism of COVID-19 is not well understood. Therefore, we analyzed gene expression profiles of COVID-19 patients to identify disease-related genes through an innovative machine learning method that enables a data-driven strategy for gene selection from a data set with a small number of samples and many candidates. Principal-component-analysis-based unsupervised feature extraction (PCAUFE) was applied to the RNA expression profiles of 16 COVID-19 patients and 18 healthy control subjects. The results identified 123 genes as critical for COVID-19 progression from 60,683 candidate probes, including immune-related genes. The 123 genes were enriched in binding sites for transcription factors NFKB1 and RELA, which are involved in various biological phenomena such as immune response and cell survival: the primary mediator of canonical nuclear factor-kappa B (NF-κB) activity is the heterodimer RelA-p50. The genes were also enriched in histone modification H3K36me3, and they largely overlapped the target genes of NFKB1 and RELA. We found that the overlapping genes were downregulated in COVID-19 patients. These results suggest that canonical NF-κB activity was suppressed by H3K36me3 in COVID-19 patient blood.

scholarly journals RankerGUI: A Computational Framework to Compare Differential Gene Expression Profiles Using Rank Based Statistics

2019 ◽  
Vol 20 (23) ◽  
pp. 6098 ◽  
Author(s):  
Amarinder Singh Thind ◽  
Kumar Parijat Tripathi ◽  
Mario Rosario Guarracino
Keyword(s):  
Gene Expression ◽  
Differential Expression ◽  
Differential Gene Expression ◽  
Web Application ◽  
Cellular Response ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Experimental Conditions ◽  
Differential Gene

The comparison of high throughput gene expression datasets obtained from different experimental conditions is a challenging task. It provides an opportunity to explore the cellular response to various biological events such as disease, environmental conditions, and drugs. There is a need for tools that allow the integration and analysis of such data. We developed the “RankerGUI pipeline”, a user-friendly web application for the biological community. It allows users to use various rank based statistical approaches for the comparison of full differential gene expression profiles between the same or different biological states obtained from different sources. The pipeline modules are an integration of various open-source packages, a few of which are modified for extended functionality. The main modules include rank rank hypergeometric overlap, enriched rank rank hypergeometric overlap and distance calculations. Additionally, preprocessing steps such as merging differential expression profiles of multiple independent studies can be added before running the main modules. Output plots show the strength, pattern, and trends among complete differential expression profiles. In this paper, we describe the various modules and functionalities of the developed pipeline. We also present a case study that demonstrates how the pipeline can be used for the comparison of differential expression profiles obtained from multiple platforms’ data of the Gene Expression Omnibus. Using these comparisons, we investigate gene expression patterns in kidney and lung cancers.

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