Unmet Need
Epigenetics is the study of biochemical modifications carrying information independent of DNA sequence, which are heritable through cell division. To date, methylation landscapes have not yet been rigorously computed.
Technology Overview
Using principles from statistical physics and information theory, JHU inventors have derived epigenetic energy landscapes from whole-genome bisulfite sequencing (WGBS) data that enabled them to quantify methylation stochasticity genome-wide using Shannon’s entropy, associating it with chromatin structure. Moreover, they considered the Jensen–Shannon distance between sample-specific energy landscapes as a measure of epigenetic dissimilarity and demonstrated its effectiveness for discerning epigenetic differences. By viewing methylation maintenance as a communications system, the inventors introduced methylation channels and showed that higher-order chromatin organization could be predicted from their informational properties. Their results provide a fundamental understanding of the information-theoretic nature of the epigenome that leads to a powerful approach for studying its role in disease and aging. This is a paradigm shifting approach to understanding the information content of the epigenome, broadly applicable to aging and cancer. It has potentially high commercial value and can be applied to predict a patient’s response to chemo- or immunotherapy.
Stage of Development
This merger of epigenetic biology and statistical physics yields many fundamental insights into the relationship between information-theoretic properties of the epigenome and nuclear organization in normal development and disease. Moreover, it provides novel methods for evaluating the informational properties of individual samples and their chromatin structure and for quantifying differences between tissue lineages, aging, and cancer at high resolution and genome-wide.
Publications:
Jenkinson, Garrett, et al. "Potential energy landscapes identify the information-theoretic nature of the epigenome." Nature genetics 49.5 (2017): 719-729.
Patents and Applications: EU3472358, AU 2017285496, JP 7066643, and US-2022-0076779
