scholarly journals TraitCorr – correlating gene expression measurements with phenotypic data

2019 ◽  
Author(s):  
Thomas Nussbaumer ◽  
Christian Wagner ◽  
Parviz Heidari

AbstractToday, transcriptomes and microarrays can be generated and analysed in high quantity. In addition, experiments often include descriptive information about each sample which needs to be compared to the gene expression profiles. The understanding of the relationships between gene expression and phenotype is introduced as new challenge in system biology. Combining expression (RNA-seq and microarray) and phenotype data could reveal the role or effects of each gene on traits. To address all these needs, the user-interface TraitCorr was developed which allows to determine genes that are significantly correlating with a selected trait. Furthermore, it allows to determine significantly correlated genes among different traits and provides visualisation and analysis possibilities.

2021 ◽  
Author(s):  
Taguchi Y-h. ◽  
Turki Turki

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.


Author(s):  
Haowei Zhang ◽  
Yujin Ding ◽  
Qin Zeng ◽  
Dandan Wang ◽  
Ganglei Liu ◽  
...  

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.


2020 ◽  
Vol 21 (3) ◽  
pp. 861 ◽  
Author(s):  
Yingdan Yuan ◽  
Bo Zhang ◽  
Xinggang Tang ◽  
Jinchi Zhang ◽  
Jie Lin

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.


2021 ◽  
Author(s):  
Jakub Jankowski ◽  
Hye Kyung Lee ◽  
Julia Wilflingseder ◽  
Lothar Hennighausen

SummaryRecently, a short, interferon-inducible isoform of Angiotensin-Converting Enzyme 2 (ACE2), dACE2 was identified. ACE2 is a SARS-Cov-2 receptor and changes in its renal expression have been linked to several human nephropathies. These changes were never analyzed in context of dACE2, as its expression was not investigated in the kidney. We used Human Primary Proximal Tubule (HPPT) cells to show genome-wide gene expression patterns after cytokine stimulation, with emphasis on the ACE2/dACE2 locus. Putative regulatory elements controlling dACE2 expression were identified using ChIP-seq and RNA-seq. qRT-PCR differentiating between ACE2 and dACE2 revealed 300- and 600-fold upregulation of dACE2 by IFNα and IFNβ, respectively, while full length ACE2 expression was almost unchanged. JAK inhibitor ruxolitinib ablated STAT1 and dACE2 expression after interferon treatment. Finally, with RNA-seq, we identified a set of genes, largely immune-related, induced by cytokine treatment. These gene expression profiles provide new insights into cytokine response of proximal tubule cells.


2020 ◽  
Vol 11 (Suppl 1) ◽  
pp. S101-S106
Author(s):  
Reza Vafaee ◽  
Abdolrahim Nikzamir ◽  
Mohhamadreza Razzaghi ◽  
Sina Rezaei Tavirani ◽  
Alireza Ahmadzadeh ◽  
...  

2020 ◽  
Vol 61 (6) ◽  
pp. 32
Author(s):  
Qing Zhang ◽  
Jian Zhang ◽  
Mengting Gong ◽  
Ruolan Pan ◽  
Yanchang Liu ◽  
...  

mSphere ◽  
2019 ◽  
Vol 4 (2) ◽  
Author(s):  
Ting Y. Wong ◽  
Jesse M. Hall ◽  
Evan S. Nowak ◽  
Dylan T. Boehm ◽  
Laura A. Gonyar ◽  
...  

ABSTRACTBordetella pertussiscauses the disease whooping cough through coordinated control of virulence factors by theBordetellavirulence gene system. Microarrays and, more recently, RNA sequencing (RNA-seq) have been used to describein vitrogene expression profiles ofB. pertussisand other pathogens. In previous studies, we have analyzed thein vitrogene expression profiles ofB. pertussis, and we hypothesize that the infection transcriptome profilein vivois significantly different from that under laboratory growth conditions. To study the infection transcriptome ofB. pertussis, we developed a simple filtration technique for isolation of bacteria from infected lungs. The work flow involves filtering the bacteria out of the lung homogenate using a 5-μm-pore-size syringe filter. The captured bacteria are then lysed to isolate RNA for Illumina library preparation and RNA-seq analysis. Upon comparing thein vitroandin vivogene expression profiles, we identified 351 and 255 genes as activated and repressed, respectively, during murine lung infection. As expected, numerous genes associated with virulent-phase growth were activated in the murine host, including pertussis toxin (PT), the PT secretion apparatus, and the type III secretion system. A significant number of genes encoding iron acquisition and heme uptake proteins were highly expressed during infection, supporting iron acquisition as critical forB. pertussissurvivalin vivo. Numerous metabolic genes were repressed during infection. Overall, these data shed light on the gene expression profile ofB. pertussisduring infection, and this method will facilitate efforts to understand how this pathogen causes infection.IMPORTANCEIn vitrogrowth conditions for bacteria do not fully recapitulate the host environment. RNA sequencing transcriptome analysis allows for the characterization of the infection gene expression profiles of pathogens in complex environments. Isolation of the pathogen from infected tissues is critical because of the large amounts of host RNA present in crude lysates of infected organs. A filtration method was developed that enabled enrichment of the pathogen RNA for RNA-seq analysis. The resulting data describe the “infection transcriptome” ofB. pertussisin the murine lung. This strategy can be utilized for pathogens in other hosts and, thus, expand our knowledge of what bacteria express during infection.


PLoS ONE ◽  
2020 ◽  
Vol 15 (8) ◽  
pp. e0237907
Author(s):  
Brianna Dufek ◽  
Daniel T. Meehan ◽  
Duane Delimont ◽  
Kevin Wilhelm ◽  
Gina Samuelson ◽  
...  

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