We seek to understand the mechanistic basis of human disease, using a combination of computational and experimental techniques.
Our techniques involve developing methods for the systematic discovery and characterization of functional elements in the human genome, the discovery and validation of the gene-regulatory circuitry controlling these elements, the use of epigenomic information for annotating regulatory regions and their activity across different cell types, and the use of comparative genomics for recognizing coding and non-coding regions of functional importance for evolutionary fitness. Topics include variation and disease, genome interpretation, gene regulation, epigenomics, and genome evolution.
Yosuke Tanigawa, MIT CSAIL and Broad Institute research scientist, received the AJHG Award for Outstanding Trainee Publication for his work on a genetic prediction model that includes a wider diversity of genetic ancestries.
New methodology improves genetic discovery up to 2.8 fold by utilizing data points that would typically be discarded given the low accuracy in quantification.
Genomics and lab studies reveal numerous findings, including a key role for Reelin amid neuronal vulnerability, and for choline and antioxidants in sustaining cognition.
MIT CSAIL and University of Tokyo researchers present GenoBoost, a polygenic scoring approach that accounts for both additive and non-additive genetic dominance effects in individuals’ health data.
A new study from MIT and collaborators highlights how heart disease affects the right atrium, revealing how it changes at single-cell resolution across various heart diseases, along with the pericardial fluid surrounding the heart.
Single-cell gene expression patterns in the brain, and evidence from follow-up experiments, reveal many shared cellular and molecular similarities that could be targeted for potential treatment.
Researchers looked at how non-coding regulatory regions are regulated in the four tissues of brain, heart, muscle, and lung, illuminating the intricate links between genetics, epigenetics, and disease mechanisms in a step towards more personalized medicine.
