Senescent Cells Transcriptome Analysis
InquiryThe progressive accumulation of senescent cells drives aging, and it may be triggered by a number of different mechanisms, including telomere wear and tear, disease gene signaling, and other causes. Moreover, cellular senescence is specific and different tissues and organs have different rates of cellular senescence, so we need more studies to increase our understanding of senescent cells.
As a unique technology expert in senescence research, CD BioSciences can provide transcriptome analysis of senescent cells, primarily by characterizing the transcriptome to understand the transcriptomic mechanisms of cellular senescence and find specific transcriptional markers in specific senescent cells.
Introduction to Transcriptional Heterogeneity of Senescent Cells
Cellular senescence is heterogeneous, including their transcriptome characteristics. It is having different transcriptomic changes that some interventions or drugs for senescence will produce different effects. That is, specific cells have different mechanisms of aging.
Fig 1. Transcriptional heterogeneity in senescent cells in vitro (Kim S and Kim C. 2021)
There are many approaches to detect specific senescent cells, including observing senescence-specific cell types in various tissues, monitoring changes in cell populations and identifying specific populations associated with senescence. We provide transcriptome analysis of senescent cells to help clients establish novel anti-aging interventions or therapeutic regimens by detecting and analyzing the transcriptome characteristics of senescent cells to provide a detailed understanding of senescent cells at the molecular level and to identify new targets for aging interventions.
Our Services
We provide RNA sequencing analysis to help researchers and biopharmaceutical companies to explore the specificity and potential biomarkers of senescent cells.
Senescent cell model construction
We construct target cell lines and culture them in appropriate media that can be set up to induce multiple mechanisms of senescence to be used when the cells are cultured to replicative failure.
RNA sequencing
Total RNA is extracted first, double-end cDNA libraries are created, and all senescence models are sequenced using Illumina to ensure the quality of the sequencing data.
Bioinformatics analysis
We carry out differential expression analysis of RNA sequencing data, do quality control for sample bias and abundance bias, and identify common features of the transcriptome of senescent cells and differentially expressed RNAs.
Submitted Results
We obtain complete transcriptome data with low error, analyze and provide more of the data results you are looking for. This includes but is not limited to the following,
- Characterization results of senescent cell models. We determine the senescence phenotype of senescent cell populations, assess senescence-related enzymatic activities to monitor the senescence process, and finally form a mature cellular senescence model for further analysis.
- Sequencing results of the transcriptome of senescent cells. Sequencing data are bioinformatically analyzed, and comparison with control data can be analyzed to obtain differential expression RNA analysis, identify senescence-associated transcripts, and validate the results.
CD BioSciences' service philosophy is one of client-centered, collaborative partnership building. We provide knowledge and technical consultation related to the aging transcriptome to help our clients solve problems and advance their research. Transcriptome sequencing guarantees the quality of our services through a sensitive and efficient technical approach and analysis process.
If you would like to find a reliable partner to assist you with your project, please feel free to contact us.
Reference
- Kim S and Kim C. Transcriptomic Analysis of Cellular Senescence: One Step Closer to Senescence Atlas. Mol Cells, 2021;44(3):136-145.
Our services are for research use only and not for any clinical use.
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We are a comprehensive technology platform company integrating aging DNA methylation, telomere, transcriptome, proteome, and metabolome research.