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  • Question about inputs for ChIP-seq

    Hey guys. I just got ChIP-seq working, and I am gearing up to sequence some more libraries. I had a question for the forum. I am sequencing ChIP DNA from the same cell type that I have already sequenced input from over 2 different cross-links. Is it common practice to sequence an input from every crosslink you ChIP from, or can I just compare the sequence data from my new ChIP libraries to the input DNA that I have already sequenced from the same cell type? Is this accepted in the field? It has been suggested to me that I do this, but it seems strange to me not to have an input with every crosslink.

    Thanks.

  • #2
    For each crosslinking you should sequence the input along with the ChIP. Experimentally, its best to keep everything in parallel as much as possible. The crosslinking and sheering are going to be different with each new input. For me, I like processing the inputs and ChIP libraries as much in parallel as possible beyond that. So, DNA isolation all the way through library prep and sequencing are done together. Though sometimes you end up with your input and some of your ChIP libraries (from the same crosslinking) being sequenced at different times due to machine problems, but you do the best you can.

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    • #3
      Input isn't really a negative control (it measures chromatin accessibility, which is of course enriched where you find transcription factors) and arguably you shouldn't be doing any input samples. I certainly wouldn't recommend spending money to get more of it.

      Is there a more biologically meaningful control you could do? Can you knock out/down your ChIP target? Do you have a different experimental treatment? A different antibody to the same target?

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      • #4
        I think what jwfoley is arguing for is some sort of biological control, while you might call inputs an experimental control. Both have validity, it just depends on what you're doing. You may want to do one or the other, or both. It sounds like you're already doing both, and I suggest you keep sequencing your inputs just incase some crosslinking/sheering differences creep in.

        Here's what the encode best practices has to say, which can be found here and has tons more useful information for those relatively new to ChIP-seq https://genome.ucsc.edu/encode/proto...e_v2_2011.pdf:

        Controls
        For both ChIP-seq and ChIP-chip, control experiments must be performed. Breakage during sonication can occur preferentially in regions of open chromatin resulting in non-uniformbackground signal (Auerbach et al., 2009). In addition, many cell lines are aneuploid and have many large regions of genomic duplications, which can heavily influence peak sizes and rankings. Control DNAs include “Input” DNA, in which DNA is isolated from cells that have been crosslinked and sonicated under conditions similar to the experimental sample or “IgG” in which control immunoprecipitations are performed using an antibody fraction (Immunoglobulin G from an unimmunized animal) that does not recognize DNA or chromatin associated proteins. In cases where factor binding to DNA is environmentally induced, (e.g. after hormone induction of the glucocorticoid receptor or when analyzing a protein expressed from an inducible promoter), a potential appropriate control is a parallel ChIP experiment done on cells in the uninduced conditions. Similarly, for epitope tagged constructs suitable controls are performed with cells lacking the epitope tag. If amplification is used to prepare the experimental sample, then the control DNA must be prepared using the same amplification procedure; note that biases in amplification can increase the chances of overrepresentation and underrepresentation of sequences. Control experiments need to be performed for each cell line, developmental stage and different condition/treatment since the open chromatin regions are likely to change under the different cell types/stages/conditions.

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        • #5
          I think what jwfoley is arguing for is some sort of biological control, while you might call inputs an experimental control.
          Better to call input a technical control. But yes, if you do a biological control, a technical control may be redundant. And if your only control is technical then your biological findings might not be very solid.

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          • #6
            A single Chip is a single experiment. You take "A" DNA and pull down a subset "B". "A" is then the control of that singular experiment. The wider experiment may contain different stages, treatments, tissues, antibodies, etc., but they all hinge on the simple put A in get B out. Then you can start comparing B1, B2 ... Bn when correcting each for A1, A2, ... An. Arguig over technical control or experimental control is largely an argument over semantics.

            My assumption is that omy567 has A1, A2 and B1, B2, but is now wondering if he can just continue with only B3 ... Bn. I would argue that's not very wise as it relaying on the assumption that cells grown separately, cross linked separately, sheered separately, run through library prep and sequencing separately will yield similar data.

            You only need maybe 1/4-1/6 of a 1x50bp HiSeq lane, which could cost as little as $100-200 in library prep and $200 sequencing. That's not a lot of money to protect yourself from batch biases.

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            • #7
              The Input is better to be included for each chromatin extraction. There are quite a lot of reasons to do so.

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              • #8
                That paper says exactly the opposite of what you're saying.

                We show that relying on input control as a normalizer is not generally appropriate
                In particular:

                However, we observed that C. elegans ChIP input control DNA sequence data (hereafter referred to as input sequence) display strong reproducible patterns (Figure 1a). These patterns do not appear to be due to cross-linking and incomplete solubilization of DNA fragments in the input extract because similar patterns are evident in published genomic DNA sequence data (7), where the DNA was deproteinated prior to fragmentation and not cross-linked (Figure 1a). The reproducibility of the patterns indicates that they are not due to random sampling variations.
                In other words, not only do you not need to do an input control for each ChIP, but you probably don't need to do an input control at all, because the biases it captures are constant across all experiments on the same genome. The biases are inherent and biological, not technical.

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                • #9
                  It is better to include input for every chip you do so that you keep everything in parallel.

                  Having said that, we have found that peak calling results have negligible differences using different input as long as it is from the same cell type. Now as long as we have one input for a particular cell line, we do not do input at all.

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