As transcriptome sequencing continues developing and sequencing costs continue falling, many biologists are now using RNA-Seq for routine transcriptome profiling, a job previously reserved for RNA profiling chips.
In the expression profiling chips that we used here each mRNA transcript is represented by a probe set, i.e. a group of oligonucleotides of around 25 nucleotides in length.
Our results confirmed the general observation that ChIP-seq usually produces a more distinctive signal profile than ChIP-chip.
Despite a combination of modern technologies such as high density single nucleotide polymorphism (SNP) panels, transcriptional profiling, ChIP-on-chip data [5], [6], together with computational approaches including eQTL [7], eQED [8], Regulatory Potential [9] and Regulatory Impact Factors [10], decoding causal transcriptional regulation remains a challenge.
This process is facilitated by various experimental high-throughput technologies such as genome sequencing, gene expression profiling, ChIP-chip/ChIP-seq assays, protein-protein interaction screens, and mass spectrometry [ 2– 4].
We hypothesized that we can utilize data from mESCs-related mRNA microarrays profiling and genome-wide transcription factor binding profiling (ChIP-seq) applied to characterize mESCs to classify genes important for ES cell self-renewal and pluripotency (MSMGs).
Then given a compendium of N gene expression profiles, ChIP-PED searches among all biological contexts with at least three samples, for contexts that are associated with the regulatory pattern of interest (e.g. TF+TG+).
For each combination of developmental stage and IP factor, three biological samples were profiled by ChIP-chip, and one of these samples was independently profiled by ChIP-seq.
They incorporated additional data into their model, taking advantage of public yeast expression profiles and ChIP-chip data.
We examined the molecular mechanisms that underlie neuronal subtype specification by characterizing REST and CoREST protein expression and target gene profiles using ChIP-chip analysis in a developmental paradigm associated with the elaboration of mature neuronal subtypes.
