Posts Tagged ‘epigenomics’

Inferring chromatin-bound protein complexes from genome-wide binding assays – Genome Research

February 26, 2017

Inferring [w. NMF] chromatin-bound protein complexes [of TFs] from [ENCODE ChIP-seq] binding assays, by @ElementoLab
http://genome.cshlp.org/content/23/8/1295.full

Giannopoulou E, Elemento O. 2013. Inferring chromatin-bound
protein complexes from genome-wide binding assays. Genome Research, Published in Advance April 3, 2013, doi: 10.1101/gr.149419.112.

This study uses nonnegative matrix factorization (NMF) of ENCODE CHIP-seq data (transcription
factors and histone modifications) to predict complexes of
transcription factors that bind DNA
together; it then assesses how these predicted complexes regulate gene expression. It goes beyond
previous studies in that it attempts to treat the TFs as complexes rather than individuals. A handful of
the predicted complexes correspond to known regulatory complexes, e.g. PRC2, and overall, the
complexes were enriched for known protein-protein interactions. Linear regression and random forest
models were then used to predict the effects of the complexes on the expression of adjacent genes. In
both models, the complexes performed better than those predicted from a scrambled TF read count
matrix. Overall, this study provides a large set of hypotheses for combinations of TFs that may
function together, as well as potential new components of known complexes.

Epigenomic alterations in localized and advanced prostate cancer – Neoplasia

November 27, 2013

Summary for:

“Epigenomic Alterations in Localized and Advanced Prostate Cancer” Lin PC, Giannopoulou E, Park K, Mosquera JM, Sboner A, Tewari AK, Garraway LA, Beltran H, Rubin MA*, Elemento O*. 2013. Epigenomic alterations in localized and advanced prostate cancer. Neoplasia

http://www.ncbi.nlm.nih.gov/pubmed/23555183

In this paper, the authors take advantage of new advances in reduced representation bisulfite sequencing, a method for measuring DNA methylation patterns genome-wide, with high coverage and
single-nucleotide resolution, to study methylation patterns in prostate cancer. Working with a prostate cancer cohort already studied with DNA-Seq and RNA-Seq analyses, the authors identified
differentially methylated regions (DMRs), comparing the methylation of prostate cancer samples to benign prostate samples. The analysis found an increase in DNA methylation in prostate cancer samples, and that the methylation was more diverse and heterogeneous compared to the patterns of benign samples. Furthermore, it was found that genes near hypermethylated DMRs tended to have decreased expression, while genes near hypomethylated DMRs tended to have increased expression. Additional analyses revealed that breakpoints associated with prostate-cancer-specific deletions, duplications, and translocations tended to be highly methylated in benign prostate tissue. Finally, a study of CpG islands at different stages of prostate cancer (benign vs. PCa vs. CRPC (castration-resistant prostate cancer)) revealed that certain islands become increasingly methylated with disease severity. The authors used this data as the basis for two classification models: one to discriminate between benign prostate tissue and PCa tissue, and another to discriminate between PCa tissue and CRPC tissue. Both models demonstrated high sensitivity and specificity, indicating that CpG islands with high discriminatory power could serve as a diagnostic basis for predicting disease aggressiveness. Finally, additional analyses revealed that breakpoints associated with
prostate-cancer-specific deletions, duplications, and translocations tended to be highly methylated in benign prostate tissue.

Table 2 : Epigenetic protein families: a new frontier for drug discovery : Nature Reviews Drug Discovery

April 16, 2012

http://www.nature.com/nrd/journal/vaop/ncurrent/fig_tab/nrd3674_T2.html