Jump to content

  • Log in with Facebook Log in with Twitter Log in with Windows Live Log In with Google      Sign In   
  • Create Account

Submit your paper to J Biol Methods today!
- - - - -

Enhancer Identification for Specific Genes

enhancers epigenetics bioinformatics histones

  • Please log in to reply
3 replies to this topic

#1 SarahLee8



  • Active Members
  • Pip
  • 13 posts

Posted 17 December 2015 - 11:14 AM

Hello all,


I had this in a different sub-forum, but I decided that it would better apply to this forum.


My lab is investigating human gene expression and epigenetics. My specific project that I'm getting started on now is focusing on enhancers.  One component of the project is looking at changes in the enrichment of histone modifications that are characteristic of enhancers (i.e. H3K27ac, H3K4me1/2, etc...) in response to a specific treatment.  We have data already that the modifications do significantly change in response to our experimental treatments (we used high resolution mass spec for that).  We also have a separate data set from an expression microarray that shows genes that have increased/decreased expression in response to our treatment.  To pick up from here, I want to first hand-pick some candidate genes from the microarray data to run qPCRs and I'm most interested in genes that are known to have associated enhancers in the literature and hopefully some extensive ENCODE data from other cell lines.  


So finally on to my specific question: what is the best way to go about mining all the literature and data out there to find the information that I want?  Honestly, I'm a little overwhelmed by the massive amount of information collected as part of ENCODE.  I've tried playing around with the tracks within the UCSC genome browser, but I have no idea what is the most efficient way to do this.  I'd like to narrow down by defined enhancers and the enhancer histone PTMs and be able to specifically search the most significantly changed genes in my lab's microarray data (ChIP-seq data, I guess?).


I appreciate any guidance that all of you amazing scientists can provide!





#2 bob1


    Thelymitra pulchella

  • Global Moderators
  • PipPipPipPipPipPipPipPipPipPip
  • 6,740 posts

Posted 17 December 2015 - 12:10 PM

Probably not the news you wanted to hear, but usually if there isn't an answer, its because no-one knows the answer.


Have you looked at the software tools page, there is a link there for tools that you might find interesting/useful for mining the data.

#3 SarahLee8



  • Active Members
  • Pip
  • 13 posts

Posted 04 January 2016 - 10:06 AM

Thank you very much for your response!


I had a feeling that was the reason for the lack of response.  I know the users on this site are very vigilant and helpful whenever possible.


I have explored that tools page, but it is probably worth a little more time.


Thank you again and Happy New Year!

#4 Michael Starr

Michael Starr


  • Active Members
  • PipPipPipPipPip
  • 59 posts

Posted 11 February 2016 - 04:37 PM

So it sounds to me like you're interested in finding correlation between increased transcription and histone modification? Because it sounded a little implied, but you didn't explicitly say you've done that yet.


What is the connection between enhancers and histone modifications here? I'm familiar with each individually, but not what they mean together.


Are you looking to map histone binding using the ChIP-seq?


How  big is your microarray data? Is it too big to just go in manually and select the highest expression genes, and then see if they have enhancers or histone modifications in ENCODE? Are you familiar with shell scripting? Because I feel like this component could be achieved with a fairly simple shell script.


Your scientific plan sounds like it's off to a good start. I think you're just leaving out a few details, so I don't entirely understand what you're looking to do.


It sounds to me like there should be bioinformatic tools to help you out (like MeV or biopython or something).

Edited by Michael Starr, 11 February 2016 - 04:37 PM.

Home - About - Terms of Service - Privacy - Contact Us

©1999-2013 Protocol Online, All rights reserved.