Logout
If you want to log out click in LogOut
Reference genes, also known as housekeeping genes, are essential for accurate gene expression analysis, as they provide stable expression levels across various experimental conditions. They are crucial for normalization in quantitative PCR (qPCR) and other gene expression techniques, enabling researchers to accurately interpret data by correcting for sample variability. Without appropriate housekeeping genes, the reliability of gene expression results can be compromised, leading to potential misinterpretation of data.
AnyGenes offers optimized qPCR arrays designed for effective normalization in gene expression studies, providing carefully validated reference gene panels tailored to diverse research needs. These arrays allow scientists to obtain more robust and reproducible data, reducing technical variation and enhancing overall confidence in gene expression findings. With AnyGenes’ specialized products, researchers can select and validate the most stable reference genes for their specific applications, advancing the quality of their gene expression research.
Discover our advanced qPCR arrays for Housekeeping Genes research.
Selecting suitable housekeeping genes requires careful consideration of the experimental context. Ideal housekeeping genes should exhibit minimal variability in expression across different cell types, tissues, and experimental treatments.
Commonly used genes for normalization include GAPDH (Glyceraldehyde-3-Phosphate Dehydrogenase), (Beta-Actin), and B2M (β2 microglobulin), though no single gene is universally suitable. For more precise results, multiple housekeeping genes are often recommended to increase accuracy.
In qPCR and gene expression analysis, housekeeping genes are used to normalize the amount of RNA or DNA in each sample, ensuring accurate quantification of target gene expression. This normalization is critical to account for variations in sample quantity and quality.
By comparing the expression levels of target genes to those of housekeeping genes, researchers can obtain relative expression values that reflect true biological changes. This approach is essential for studying gene regulation, cellular responses to stimuli, and the effects of genetic modifications.
When selecting a housekeeping gene, consider the following factors:
Researchers must validate housekeeping genes for each specific experiment, considering factors such as tissue type, treatment conditions, and experimental design.
Housekeeping genes are applied across numerous research areas, including cancer biology, immunology, and developmental studies, where accurate gene expression measurements are critical. By ensuring consistent data interpretation, reference genes contribute significantly to advancements in biomarker discovery, drug development, and understanding of disease mechanisms.
Scientific data is only as powerful as the analysis behind it.
AnyGenes® provides a dedicated data analysis tool specifically developed for SignArrays® pathway panels.
What does it allow you to do?
Developed on Excel (compatible with 2007+), the software is user-friendly and requires no advanced bioinformatics skills.
Customize your own signaling pathways (SignArrays®) with the factors of your choice!
Simply download and complete our Personalized SignArrays® information file
and send it at
[email protected]
to initiate your project.
| Signaling Pathways | Product ref | Informations |
|---|---|---|
Reference Genes | RG1H1 |
|
Reference Genes | RG2H1 |
| Signaling Pathways | Product ref | Informations |
|---|---|---|
Reference Genes | RG1M1 |
| Signaling Pathways | Product ref | Informations |
|---|---|---|
Reference Genes | ******* |
Biomarker list in progress. |
| Signaling Pathways | Product ref | Informations |
|---|---|---|
Reference Genes | ******* |
Biomarker list in progress. |
Looking for more answers? Visit our Help & FAQ section to find detailed informations about our products, services, and technical support.
1. Joshi CJ, et al. What are housekeeping genes? PLoS Comput Biol. (2022)13;18(7):e1010295.
2. da Conceição Braga L, et al. Identification of best housekeeping genes for the normalization of RT-qPCR in human cell lines. Acta Histochem. (2022);124(1):151821.
3. Curis E, et al. Selecting reference genes in RT-qPCR based on equivalence tests: a network based approach. Sci Rep. (2019)7;9(1):16231.