ChIP-Seq, which combines chromatin immunoprecipitation (ChIP) with ultrahigh-throughput massively parallel sequencing, is increasingly being used for mapping protein-DNA interactions in-vivo on a genome-scale. Typically, short sequence reads from ChIP-Seq are mapped to a reference genome for further analysis. Although genomic regions enriched with mapped reads could be inferred as approximate binding regions, short read lengths (~25-50nt) pose challenges for determining the exact binding sites within these regions. Here, we present SISSRs (Site Identification from Short Sequence Reads), a novel algorithm for precise identification of binding sites from short reads generated from ChIP-Seq experiments. The sensitivity and specificity of SISSRs are demonstrated by applying it on ChIP-Seq data for three widely studied and well-characterized human transcription factors: CTCF, NRSF, and STAT1. We identified 26184, 5813, and 73956 binding sites for CTCF, NRSF, and STAT1 proteins respectively, which is 32%, 299%, and 78% more than that inferred previously for the respective proteins. Motif analysis revealed that an overwhelming majority of the identified binding sites contained the previously established consensus binding sequence for the respective proteins, thus attesting for SISSRs' accuracy. SISSRs' sensitivity and precision facilitated further analyses of ChIP-Seq data revealing interesting insights, which we believe will serve as a guidance for designing ChIP-Seq experiments to map in vivo protein-DNA interactions. We also show that tag densities at the binding sites are a good indicator of protein-DNA binding affinity, which could be used to distinguish and characterize strong and weak binding sites. Using tag density as an indicator of DNA binding affinity, we have identified core residues within the NRSF and CTCF binding sites that are critical for a stronger DNA binding.
of in vivo protein-DNA binding sites from ChIP-Seq data