I am preparing ChIP-seq libraries for Illumina multiplexing. I have large amount of the ChIP-input DNA compared to the ChIP-output. I wonder if it is better to keep the DNA amount for library preps low, similar for all samples and use the same number of PCR cycles for all or use more DNA for the Inputs and adapt the number of PCR cycles individually according to how much DNA I have (e.g. 5 cycles only for ChIP-Input using 100ng DNA and 11 cycles using 1ng for ChIP-output sample).
I would recommend to start the Library preparation with the same amount of DNA for the samples that you would like to compare. So I would use the same amount of DNA for the ChIP sample and its correspondong input. In addition, using 1 ng of DNA to start the Library preparation is still a regular amount of DNA for ChIP-seq libraries.
I hope it helps. Please feel free to contact me if you need further information
https://www.diagenode.com/p/microplex-library-preparation-kit-v2-x12-12-indices-12-rxns
I would recommend to start the Library preparation with the same amount of DNA for the samples that you would like to compare. So I would use the same amount of DNA for the ChIP sample and its correspondong input. In addition, using 1 ng of DNA to start the Library preparation is still a regular amount of DNA for ChIP-seq libraries.
I hope it helps. Please feel free to contact me if you need further information
https://www.diagenode.com/p/microplex-library-preparation-kit-v2-x12-12-indices-12-rxns
Thank you all for helpful and clear answers! One more question to this topic is whether to sequence input under two indexes instead of one to reach a better coverage. First, it is MNase-seq sample that could inform about nuleosome positions and second, it may require more sequencing compared to local peaks in ChIP to cover the genome.
You should use the equal amount of DNA from your samples in all your libraries, so in my view, you should make your input control lower in amount so that it equals your ChIP amount of DNA.
Equal amount of DNA would probably have equal distribution of biases, that would ease the analysis of high throughput data
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