Analysis of optimized DNase-seq reveals intrinsic bias in transcription factor footprint identification
He, Housheng Hansen
Hu, Sheng'en Shawn
Rao, Prakash K.
Liu, X. Shirley
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CitationHe, H. H., C. A. Meyer, S. S. Hu, M. Chen, C. Zang, Y. Liu, P. K. Rao, et al. 2014. “Analysis of optimized DNase-seq reveals intrinsic bias in transcription factor footprint identification.” Nature methods 11 (1): 73-78. doi:10.1038/nmeth.2762. http://dx.doi.org/10.1038/nmeth.2762.
AbstractDNase-seq is a powerful technique for identifying cis-regulatory elements across the genome. We studied the key experimental parameters to optimize the performance of DNase-seq. We found that sequencing short 50-100bp fragments that accumulate in long inter-nucleosome linker regions is more efficient for identifying transcription factor binding sites than using longer fragments. We also assessed the potential of DNase-seq to predict transcription factor occupancy through the generation of nucleotide-resolution transcription factor footprints. In modeling the sequence-specific DNaseI cutting bias we found a surprisingly strong effect that varied over more than two orders of magnitude. This confounds DNaseI footprint analysis to the extent that the nucleotide resolution cleavage patterns at most transcription factor binding sites are derived from intrinsic DNaseI cleavage bias rather than from specific protein-DNA interactions. In contrast, quantitative comparison of DNaseI hypersensitivity between states can predict transcription factor occupancy associated with particular biological perturbations.
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