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Epigenomics - ChIP-Seq, BS-Seq, etc.

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  • Epigenomics - ChIP-Seq, BS-Seq, etc.

    Thought I would start an epigenomics thread in light of ChIP-Seq papers and this recent one from Steve Jacobsen's group here. No questions or commentary from me... I'm busy trying to wade my way through the 54 pages of supplementary data!

    Shotgun bisulphite sequencing of the Arabidopsis genome reveals DNA methylation patterning

    Shawn J. Cokus, Suhua Feng, Xiaoyu Zhang, Zugen Chen, Barry Merriman, Christian D. Haudenschild, Sriharsa Pradhan, Stanley F. Nelson, Matteo Pellegrini & Steven E. Jacobsen
    Cytosine DNA methylation is important in regulating gene expression and in silencing transposons and other repetitive sequences1, 2. Recent genomic studies in Arabidopsis thaliana have revealed that many endogenous genes are methylated either within their promoters or within their transcribed regions, and that gene methylation is highly correlated with transcription levels3, 4, 5. However, plants have different types of methylation controlled by different genetic pathways, and detailed information on the methylation status of each cytosine in any given genome is lacking. To this end, we generated a map at single-base-pair resolution of methylated cytosines for Arabidopsis, by combining bisulphite treatment of genomic DNA with ultra-high-throughput sequencing using the Illumina 1G Genome Analyser and Solexa sequencing technology6. This approach, termed BS-Seq, unlike previous microarray-based methods, allows one to sensitively measure cytosine methylation on a genome-wide scale within specific sequence contexts. Here we describe methylation on previously inaccessible components of the genome and analyse the DNA methylation sequence composition and distribution. We also describe the effect of various DNA methylation mutants on genome-wide methylation patterns, and demonstrate that our newly developed library construction and computational methods can be applied to large genomes such as that of mouse.

  • #2
    hey !

    I am very interested in chip SEQ as well, and looking at the Johnson paper and some sample data.

    hope to kindle some good discussion here...
    --
    bioinfosm

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    • #3
      That's pretty cool.

      I'd written an aligner to do something very similar to this, but it turned out to be pretty clunky. In the end, I didn't do much with it, though (incidentally) I'll be cannibalizing some of the routines tomorrow for another aligner. Good fun.

      Still, efficiently aligning 36-mers with degenerate positions accurately to a whole mammalian genome is not a trivial task. It's impressive that they've been able to do it.
      The more you know, the more you know you don't know. —Aristotle

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      • #4
        Originally posted by bioinfosm View Post
        hey !

        I am very interested in chip SEQ as well, and looking at the Johnson paper and some sample data.

        hope to kindle some good discussion here...
        Hi Bioinfosm and apfejes

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        • #5
          Well, I've had a good look at the Jacobsen groups paper now. The reads with ambiguous location are scored and assigned in a maximum likelihood fashion to multiple locations. This reminds me of the maximum likelihood approaches used in non-parametric linkage analysis.

          I'm still trying to get my head around which is a better approach. Does one conservatively drop all ambiguous reads and introduce bias by not assigning reads as often to repeat sequences and common CpG containing promoter motifs, or do you take an inclusive approach as in the above paper and introduce a layer of averaged noise across repeats and common motifs? In both instances relative comparison between a clinical sample and a "normal" seems like the preferred approach instead of trying to gauge absolute methylation status.

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          • #6
            Does anybody know where I can grab some public BS-Seq data? I'll be scouring the web for some. If I do find any I suppose it will help to post the location here.

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            • #7
              Hey Zee...see if this works for you:

              http://epigenomics.mcdb.ucla.edu/BS-Seq/download.html

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              • #8
                Thanks, but I already downloaded that one a few months back after reading the paper. The size of all those files was daunting but I suppose I'm gonna need to look deeper.

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                • #9
                  A new paper describing some serious mathematical wizardry to find chromatin signatures. Very interesting learning approach:

                  ChromaSig: A Probabilistic Approach to Finding Common Chromatin Signatures in the Human Genome

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                  • #10
                    Wow, that paper is awesome :-).

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                    • #11
                      hi sci_guy and others, I thought of activating this thread again. There is an algorithm for methylation analysis called Batman. See Down et al. (2008) Nature Biotechnology "A Bayesian deconvolution strategy for immunoprecipitation-based DNA methylome analysis"


                      Cheers

                      Dave

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                      • #12
                        For BS-Seq analysis, this thread is relevant http://seqanswers.com/forums/showthread.php?t=5502

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                        • #13
                          Hi, I am a molecular biologist and I don't have any info about BS-Seq method!!, How can I find all relevant information about it, the experimental protocol and analysis one? Is it possible for me to run a project on genome wide methylation by using BS-seq alone? Actually I mean does it need collaboration of bioinformatics specialist? Could you give me a general scheme and direct me to detailed protocols?

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                          • #14
                            Can you be more specific? What is your budget, what is the organism, are you doing comparisons? Are you doing whole genome BS-seq or some form of complexity reduction, such as reduced representation BS-Seq (RRBS)?

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