For this purpose we focused on 5 active (H3K4me1, H3K4me2, H3K4me3, H3K9ac, H3K27ac) and 2 repressive (H3K9me3, H3K27me3) histone modifications profiles in NHEK cells that have been generated by the ENCODE consortium [ 31].
In order to assess the effects of adequate levels of selenium and folate supplementation on histone modifications profiles in the liver previously reported methods [ 70, 71] were modified in order to significantly increase the concentration of nuclear proteins by combining both the nuclear pellet and supernatant.
At the single gene level we found many differences in histone modification profiles, in particular between monocytes and in vitro cultivated cells, which correlate with their transcriptional changes.
In order to evaluate their importance in colorectal cancer (CRC), we generated the first genome-wide histone modification profiles in paired normal colon mucosa and tumor samples.
Thus, comparisons of the MD-resistant and susceptible lines revealed innate differences in histone modification profiles in addition to variations induced by MDV infection.
Previously, we explored the genome-wide histone modification profiles in the human primary T cells extensively and sought the functional significance of specific domains with histone modification islands [ 3, 4, 17, 18].
The histone modification profiles in bin sizes of 100 bp between −1 and +1 kb along these elements are also observed to be different from the random set (Supporting Information, Figure S1, A and B, blue vs. red).
Our data describe several differences of H3K4me3 modification profiles in monocytes, macrophages and DCs but also suggest that the chromatin status of functionally important gene clusters is coordinately modified.
In this work we generated the first coupled normal-tumor histone modification profiles in CRC, one of the cancer types with highest incidence in developed countries, that should provide a valuable resource for future chromatin studies with CRC and/or gastrointestinal focus.
Chimira outperforms all of these tools in total execution speed and aims to facilitate simple, fast and reliable analysis of small RNA-Seq data allowing also, for the first time, identification of global microRNA modification profiles in a simple intuitive interface.
Using histone modification profiles (in 100-bp bins) between −2 and +2 kb around the exon intron boundaries, we were able to classify all known boundaries from genic background with an accuracy of 87% in H (AUCall = 0.94) or 85.5% in IMR90 (AUCall = 0.93).
