Assessing stationary distributions derived from chromatin contact maps

摘要

The spatial configuration of chromosomes is essential to various cellular processes, notably gene regulation. Conversely, architecture related alterations, such as translocations and gene fusions, are often cancer drivers. Accordingly, eliciting chromatin conformation is important. Such elicitation had been challenging due to chromatin compaction, dynamics and scale. However, the emergence of the suite of chromatin conformation capture assays, in particular Hi-C, generated new details of chromatin structure and spawned a number of subsequent biological findings [ , , , , ]. Many of these findings have directly resulted from analyses of interaction or contact level data generated by Hi-C assays. Such data, usually obtained from bulk cell populations, record the frequency with which pairs of genomic loci (or bins thereof) are cross-linked, indicating spatial proximity of those loci within the nucleus. A less common Hi-C analysis paradigm proceeds by first converting these contact frequencies into distances, this transformation often invoking inverse power-laws [ , , , , ]), and then generating a putative three dimensional (3D) reconstruction of the associated chromatin configuration via variants of multi-dimensional scaling (MDS). Such 3D reconstruction has been shown to enrich analyses based solely on the underlying contact map, these deriving, in part, from superposing genomic features. Examples include identifying co-localized genomic landmarks such as early replication origins [ , ], expression gradients and co-localization of virulence genes in the malaria parasite [ ], the impact of spatial organization on double strand break repair [ ], and elucidation of ‘3D hotspots’ corresponding to overlaid ChIP-Seq transcription factor maxima, revealing novel regulatory interactions [ ].