Emerson, D. J. | Search bioRxiv

bioRxiv2017

Genetic drivers of repeat expansion disorders localize to 3-D chromatin domain boundaries

More than 25 inherited neurological disorders are caused by the unstable expansion of repetitive DNA sequences termed short tandem repeats (STRs). A fundamental unresolved question is why specific STRs are susceptible to unstable expansion leading to severe pathology, whereas tens of thousands of normal-length repeat tracts across the human genome are relatively stable. Here, we unexpectedly discover that nearly all STRs associated with repeat expansion diseases are located at boundaries demarcating 3-D chromatin domains. We find that boundaries exhibit markedly higher CpG island density compared to loci internal to domains. Importantly, disease-associated STRs are specifically localized to ultra-dense CpG island-rich boundaries, suggesting that these loci might be hotspots for epigenetic instability and topological disruption upon unstable expansion. In Fragile X Syndrome, mutation-length expansion at the Fmr1 gene results in severe disruption of the boundary between TADs. Our data uncover higher-order chromatin architecture as a new dimension in understanding the mechanistic basis of repeat expansion disorders.

genomics↗

bioRxiv2016

Detecting hierarchical 3-D genome domain reconfiguration with network modularity

Mammalian genomes are folded in a hierarchy of topologically associating domains (TADs), subTADs and looping interactions. The nested nature of chromatin domains has rendered it challenging to identify a sensitive and specific metric for detecting subTADs and quantifying their dynamic reconfiguration across cellular states. Here, we apply graph theoretic principles to quantify hierarchical folding patterns in high-resolution chromatin topology maps. We discover that TADs can be accurately detected using a Louvain-like locally greedy algorithm to maximize network modularity. By varying a resolution parameter in the modularity quality function, we accurately partition the mouse genome across length scales into a hierarchical nested structure of network communities exhibiting a wide range of sizes. To distinguish high probability subTADs from the full detected set, we developed and applied a new hierarchical spatial variance minimization method. Moreover, we identified a large number of dynamically altered communities between pluripotent embryonic stem cells and multipotent neural progenitor cells. Cell type specific boundaries correlate with trends in dynamic occupancy of the architectural protein CTCF, thereby validating their biological relevance. Together, these data demonstrate the utility of metrics from network science in quantifying a nested hierarchy of dynamic 3D chromatin communities across length scales. Our findings are significant toward unraveling the link between higher-order genome folding and gene expression during healthy development and the deregulation of molecular pathways linked to disease.

genomics↗