Add like
Add dislike
Add to saved papers

Systematic Analysis of the Determinants of Gene Expression Noise in Embryonic Stem Cells.

Cell Systems 2017 November 23
Isogenic cells in a common environment show substantial cell-to-cell variation in gene expression, often referred to as "expression noise." Here, we use multiple single-cell RNA-sequencing datasets to identify features associated with high or low expression noise in mouse embryonic stem cells. These include the core promoter architecture of a gene, with CpG island promoters and a TATA box associated with low and high noise, respectively. High noise is also associated with "conflicting" chromatin states-the absence of transcription-associated histone modifications or the presence of repressive ones in active genes. Genes regulated by pluripotency factors through super-enhancers show high and correlated expression variability, consistent with fluctuations in the pluripotent state. Together, our results provide an integrated view of how core promoters, chromatin, regulation, and pluripotency fluctuations contribute to the variability of gene expression across individual stem cells.

Full text links

We have located links that may give you full text access.
Can't access the paper?
Try logging in through your university/institutional subscription. For a smoother one-click institutional access experience, please use our mobile app.

Related Resources

For the best experience, use the Read mobile app

Mobile app image

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app

All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.

By using this service, you agree to our terms of use and privacy policy.

Your Privacy Choices Toggle icon

You can now claim free CME credits for this literature searchClaim now

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app