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Abstract
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.
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