Epigenome


MATCHER: manifold alignment reveals correspondence between single cell transcriptome and epigenome dynamics

Our next meeting will be at 1pm on Oct 29th, in room 4160 of the Discovery building. Our Selected paper is MATCHER: manifold alignment reveals correspondence between single cell transcriptome and epigenome dynamics.
The abstract is as follows.

Single cell experimental techniques reveal transcriptomic and epigenetic heterogeneity among cells, but how these are related is unclear. We present MATCHER, an approach for integrating multiple types of single cell measurements. MATCHER uses manifold alignment to infer single cell multi-omic profiles from transcriptomic and epigenetic measurements performed on different cells of the same type. Using scM&T-seq and sc-GEM data, we confirm that MATCHER accurately predicts true single cell correlations between DNA methylation and gene expression without using known cell correspondences. MATCHER also reveals new insights into the dynamic interplay between the transcriptome and epigenome in single embryonic stem cells and induced pluripotent stem cells.

We welcome all who can join us for this discussion. Feel free to begin that discussion in the comments section below.


Genome-scale high-resolution mapping of activating and repressive nucleotides in regulatory regions

Our next meeting will be at 3:00 on December 5th, in room 3160 of the Discovery building. Our Selected paper is Genome-scale high-resolution mapping of activating and repressive nucleotides in regulatory regions.
The abstract is as follows.

Massively parallel reporter assays (MPRAs) enable nucleotide-resolution dissection of transcriptional regulatory regions, such as enhancers, but only few regions at a time. Here we present a combined experimental and computational approach, Systematic high-resolution activation and repression profiling with reporter tiling using MPRA (Sharpr-MPRA), that allows high-resolution analysis of thousands of regions simultaneously. Sharpr-MPRA combines dense tiling of overlapping MPRA constructs with a probabilistic graphical model to recognize functional regulatory nucleotides, and to distinguish activating and repressive nucleotides, using their inferred contribution to reporter gene expression. We used Sharpr-MPRA to test 4.6 million nucleotides spanning 15,000 putative regulatory regions tiled at 5-nucleotide resolution in two human cell types. Our results recovered known cell-type-specific regulatory motifs and evolutionarily conserved nucleotides, and distinguished known activating and repressive motifs. Our results also showed that endogenous chromatin state and DNA accessibility are both predictive of regulatory function in reporter assays, identified retroviral elements with activating roles, and uncovered ‘attenuator’ motifs with repressive roles in active chromatin.


DeepChrome: Deep-learning for predicting gene expression from histone modifications

Our next meeting will be at 3:00 on November 21st, in room 3160 of the Discovery building. Our Selected paper is DeepChrome: Deep-learning for predicting gene expression from histone modifications.
The abstract is as follows.

Motivation: Histone modifications are among the most important factors that control gene regulation. Computational methods that predict gene expression from histone modification signals are highly desirable for understanding their combinatorial effects in gene regulation. This knowledge can help in developing ‘epigenetic drugs’ for diseases like cancer. Previous studies for quantifying the relationship between histone modifications and gene expression levels either failed to capture combinatorial effects or relied on multiple methods that separate predictions and combinatorial analysis. This paper develops a unified discriminative framework using a deep convolutional neural network to classify gene expression using histone modification data as input. Our system, called DeepChrome, allows automatic extraction of complex interactions among important features. To simultaneously visualize the combinatorial interactions among histone modifications, we propose a novel optimization-based technique that generates feature pattern maps from the learnt deep model. This provides an intuitive description of underlying epigenetic mechanisms that regulate genes.
Results: We show that DeepChrome outperforms state-of-the-art models like Support Vector Machines and Random Forests for gene expression classification task on 56 different cell-types from REMC database. The output of our visualization technique not only validates the previous observations but also allows novel insights about combinatorial interactions among histone modification marks, some of which have recently been observed by experimental studies.

We welcome all who can join us for this discussion. Feel free to begin that discussion in the comments section below.


Epigenomic Co-localization and Co-evolution Reveal a Key Role for 5hmC as a Communication Hub in the Chromatin Network of ESCs

Our selected paper for this week is titled Epigenomic Co-localization and Co-evolution Reveal a Key Role for 5hmC as a Communication Hub in the Chromatin Network of ESCs, from Cell.The abstract is as follows:

Epigenetic communication through histone and cytosine modifications is essential for gene regula- tion and cell identity. Here, we propose a framework that is based on a chromatin communication model to get insight on the function of epigenetic modifica- tions in ESCs. The epigenetic communication network was inferred from genome-wide location data plus extensive manual annotation. Notably, we found that 5-hydroxymethylcytosine (5hmC) is the most-influential hub of this network, connecting DNA demethylation to nucleosome remodeling complexes and to key transcription factors of plurip- otency. Moreover, an evolutionary analysis revealed a central role of 5hmC in the co-evolution of chro- matin-related proteins. Further analysis of regions where 5hmC co-localizes with specific interactors shows that each interaction points to chromatin remodeling, stemness, differentiation, or meta- bolism. Our results highlight the importance of cyto- sine modifications in the epigenetic communication of ESCs.

Feel free to begin our discussion in the comments section below. Our meeting will be at 12:30 PM in room 3160 of the Discovery building on July 18th.