scholarly journals A human tissue‐specific transcriptomic analysis reveals a complex relationship between aging, cancer, and cellular senescence

Aging Cell ◽  
2019 ◽  
Vol 18 (6) ◽  
Author(s):  
Kasit Chatsirisupachai ◽  
Daniel Palmer ◽  
Susana Ferreira ◽  
João Pedro Magalhães
Keyword(s):  
Cellular Senescence ◽  
Human Tissue ◽  
Transcriptomic Analysis ◽  
Complex Relationship ◽  
Tissue Specific

scholarly journals Understanding multicellular function and disease with human tissue-specific networks

2015 ◽  
Vol 47 (6) ◽  
pp. 569-576 ◽  
Author(s):  
Casey S Greene ◽  
Arjun Krishnan ◽  
Aaron K Wong ◽  
Emanuela Ricciotti ◽  
Rene A Zelaya ◽  
...  
Keyword(s):  
Human Tissue ◽  
Tissue Specific

Tissue specific expression and serum levels of human tissue factor in patients with urological cancer

2003 ◽  
Vol 193 (1) ◽  
pp. 65-73 ◽  
Author(s):  
Yvonne Förster ◽  
Axel Meye ◽  
Sybille Albrecht ◽  
Matthias Kotzsch ◽  
Susanne Füssel ◽  
...  
Keyword(s):  
Tissue Factor ◽  
Human Tissue ◽  
Serum Levels ◽  
Urological Cancer ◽  
Specific Expression ◽  
Tissue Specific ◽  
Tissue Specific Expression

scholarly journals TissueCoCoPUTs: Novel Human Tissue-Specific Codon and Codon-Pair Usage Tables Based on Differential Tissue Gene Expression

2020 ◽  
Vol 432 (11) ◽  
pp. 3369-3378 ◽  
Author(s):  
Jacob Kames ◽  
Aikaterini Alexaki ◽  
David D. Holcomb ◽  
Luis V. Santana-Quintero ◽  
John C. Athey ◽  
...  
Keyword(s):  
Gene Expression ◽  
Human Tissue ◽  
Tissue Specific ◽  
Codon Pair ◽  
Differential Tissue ◽  
Tissue Gene Expression

scholarly journals Biclustering of transcriptome sequencing data reveals human tissue-specific circular RNAs

BMC Genomics ◽  
2018 ◽  
Vol 19 (S1) ◽  
Author(s):  
Yu-Chen Liu ◽  
Yu-Jung Chiu ◽  
Jian-Rong Li ◽  
Chuan-Hu Sun ◽  
Chun-Chi Liu ◽  
...  
Keyword(s):  
Human Tissue ◽  
Transcriptome Sequencing ◽  
Circular Rnas ◽  
Sequencing Data ◽  
Tissue Specific

scholarly journals Scope and limitations of yeast as a model organism for studying human tissue-specific pathways

2015 ◽  
Vol 9 (1) ◽  
Author(s):  
Shahin Mohammadi ◽  
Baharak Saberidokht ◽  
Shankar Subramaniam ◽  
Ananth Grama
Keyword(s):  
Human Tissue ◽  
Model Organism ◽  
Tissue Specific

scholarly journals Transcriptomic Analysis and Specific Expression of Transcription Factor Genes in the Root and Sporophyll of Dryopteris fragrans (L.) Schott

2020 ◽  
Vol 21 (19) ◽  
pp. 7296
Author(s):  
Lingling Chen ◽  
Dongrui Zhang ◽  
Chunhua Song ◽  
Hemeng Wang ◽  
Xun Tang ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Transcription Factors ◽  
Glandular Trichomes ◽  
Transcriptomic Analysis ◽  
Specific Gene ◽  
Specific Expression ◽  
Tissue Specific ◽  
Transcription Factor Genes ◽  
Dryopteris Fragrans ◽  
Different Tissues

Background: Dryopteris fragrans, which is densely covered with glandular trichomes, is considered to be one of the ferns with the most medicinal potential. The transcriptomes from selected tissues of D. fragrans were collected and analyzed for functional and comparative genomic studies. The aim of this study was to determine the transcriptomic characteristics of wild D. fragrans sporangium in tissues from the SR (root), SL (sporophyll), and TRL (sporophyll with glandular trichomes removed). Results: Cluster analysis identified genes that were highly expressed in an organ-specific manner according to read mapping, feature counting, and normalization. The functional map identified gene clusters that can uniquely describe the function of each tissue. We identified a group of three tissue-specific transcription factors targeting the SL, SR, and TRL. In addition, highly expressed transcription factors (TFs) were found in each tissue-specific gene cluster, where ERF and bHLH transcription factors were the two types showing the most distinct expression patterns between the three different tissues. The specific expression of transcription factor genes varied between the different types of tissues. The numbers of transcription factors specifically expressed in the roots and sporophylls were 60 and 30, respectively, while only seven were found for the sporophylls with glandular trichomes removed. The expression of genes known to be associated with the development of glandular trichomes in flowering plants, including MIXTA, ATML1, and MYB106, were also validated and are discussed. In particular, a unigene encoding MIXTA was identified and exhibited the highest expression level in SL in D. fragrans. Conclusions: This study is the first report of global transcriptomic analysis in different tissues of D. fragrans, and the first to discuss these findings in the context of the development of homologous glandular trichomes. These results set the stage for further research on the development, stress resistance, and secondary metabolism of D. fragrans glandular trichomes.

scholarly journals Analysis of the Human Tissue-specific Expression by Genome-wide Integration of Transcriptomics and Antibody-based Proteomics

2013 ◽  
Vol 13 (2) ◽  
pp. 397-406 ◽  
Author(s):  
Linn Fagerberg ◽  
Björn M. Hallström ◽  
Per Oksvold ◽  
Caroline Kampf ◽  
Dijana Djureinovic ◽  
...  
Keyword(s):  
Human Tissue ◽  
Specific Expression ◽  
Tissue Specific ◽  
Tissue Specific Expression ◽  
Genome Wide

scholarly journals A convex optimization approach for identification of human tissue-specific interactomes

2016 ◽  
Author(s):  
Shahin Mohammadi ◽  
Ananth Grama
Keyword(s):  
Human Tissue ◽  
Drug Targets ◽  
Protein Complexes ◽  
Disease Genes ◽  
Optimization Approach ◽  
Cell Type Specificity ◽  
Tissue Specific ◽  
Parkinson’S Diseases ◽  
Coordinated Expression ◽  
Validation Tests

AbstractMotivation:Analysis of organism-specific interactomes has yielded novel insights into cellular function and coordination, understanding of pathology, and identification of markers and drug targets. Genes, however, can exhibit varying levels of cell-type specificity in their expression, and their coordinated expression manifests in tissue-specific function and pathology. Tissue-specific/ selective interaction mechanisms have significant applications in drug discovery, as they are more likely to reveal drug targets. Furthermore, tissue-specific transcription factors (tsTFs) are significantly implicated in human disease, including cancers. Finally, disease genes and protein complexes have the tendency to be differentially expressed in tissues in which defects cause pathology. These observations motivate the construction of refined tissue-specific interactomes from organism-specific interactomes.Results:We present a novel technique for constructing human tissue-specific interactomes. Using a variety of validation tests (ESEA, GO Enrichment, Disease-Gene Subnetwork Compactness), we show that our proposed approach significantly outperforms state of the art techniques. Finally, using case studies of Alzheimer’s and Parkinson’s diseases, we show that tissue-specific interactomes derived from our study can be used to construct pathways implicated in pathology and demonstrate the use of these pathways in identifying novel targets.Availability:http://www.cs.purdue.edu/homes/mohammas/projects/ActPro.html

scholarly journals A Human Tissue-Specific Transcriptomic Analysis Reveals that Ageing Hinders Cancer and Boosts Cellular Senescence

2019 ◽  
Author(s):  
Kasit Chatsirisupachai ◽  
Daniel Palmer ◽  
Susana Ferreira ◽  
João Pedro de Magalhães
Keyword(s):  
Cellular Senescence ◽  
Opposite Direction ◽  
Meta Analysis ◽  
Differentially Expressed ◽  
Complex Relationship ◽  
Human Tissues ◽  
Gene Sets ◽  
Ageing Processes ◽  
Transcriptomic Changes ◽  
The Relationship

AbstractAgeing is the biggest risk factor for cancer, but the mechanisms linking these two processes remain unclear. We compared genes differentially expressed with age and genes differentially expressed in cancer among nine human tissues. In most tissues, ageing and cancer gene expression surprisingly changed in the opposite direction. These overlapping gene sets were related to several processes, mainly cell cycle and the immune system. Moreover, cellular senescence signatures derived from a meta-analysis changed in the same direction as ageing and in the opposite direction of cancer signatures. Therefore, transcriptomic changes in ageing and cellular senescence might relate to a decrease in cell proliferation, while cancer transcriptomic changes shift towards an increase in cell division. Our results highlight the complex relationship between ageing, cancer and cellular senescence and suggest that in most human tissues ageing processes and senescence act in tandem while being detrimental to cancer. Our work challenges the traditional view concerning the relationship between cancer and ageing and suggests that ageing processes may hinder cancer development.

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