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A compendium of chromatin contact maps reflecting regulation by chromatin remodelers in budding yeast

ABSTRACT: We herein employ in situ Hi-C with an auxin-inducible degron (AID) system to examine the effect of chromatin remodeling on 3D genome organization in yeast. Eight selected ATP-dependent chromatin remodelers representing various subfamilies contribute to 3D genome organization differently. Among the studied remodelers, the temporary depletions of Chd1p, Swr1p, and Sth1p (a catalytic subunit of the Remodeling the Structure of Chromatin [RSC] complex) cause the most significant defects in intra-chromosomal contacts, and the regulatory roles of these three remodelers in 3D genome organization differ depending on the chromosomal context and cell cycle stage. Furthermore, even though Chd1p and Isw1p are known to share functional similarities/redundancies, their depletions lead to distinct effects on 3D structures. The RSC and cohesin complexes also differentially modulate 3D genome organization within chromosome arm regions, whereas RSC appears to support the function of cohesin in centromeric clustering at G2 phase. Our work suggests that the ATP-dependent chromatin remodelers control the 3D genome organization of yeast through their chromatin-remodeling activities. The effect of ATP-dependent chromatin remodelers on 3D genome organization has not been well studied. Here the authors employ in situ Hi-C with an auxin-inducible degron system to degrade chromatin remodelers in yeast to find that the 3D structure of chromatin collapses in their absence. The chromatin remodeling can modulate 3D architecture depending on chromosomal context and cell cycle stage.

SUBMITTER: Jo H

PROVIDER: S-EPMC8569116 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BACKGROUND:The spatial configuration of chromosomes is essential to various cellular processes, notably gene regulation, while architecture related alterations, such as translocations and gene fusions, are often cancer drivers. Thus, eliciting chromatin conformation is important, yet challenging due to compaction, dynamics and scale. However, a variety of recent assays, in particular Hi-C, have generated new details of chromatin structure, spawning a number of novel biological findings. Many findings have resulted from analyses on the level of native contact data as generated by the assays. Alternatively, reconstruction based approaches often proceed by first converting contact frequencies into distances, then generating a three dimensional (3D) chromatin configuration that best recapitulates these distances. Subsequent analyses can enrich contact level analyses via superposition of genomic attributes on the reconstruction. But, such advantages depend on the accuracy of the reconstruction which, absent gold standards, is inherently difficult to assess. Attempts at accuracy evaluation have relied on simulation and/or FISH imaging that typically features a handful of low resolution probes. While newly advanced multiplexed FISH imaging offers possibilities for refined 3D reconstruction accuracy evaluation, availability of such data is limited due to assay complexity and the resolution thereof is appreciably lower than the reconstructions being assessed. Accordingly, there is demand for new methods of reconstruction accuracy appraisal. RESULTS:Here we explore the potential of recently proposed stationary distributions, hereafter StatDns, derived from Hi-C contact matrices, to serve as a basis for reconstruction accuracy assessment. Current usage of such StatDns has focussed on the identification of highly interactive regions (HIRs): computationally defined regions of the genome purportedly involved in numerous long-range intra-chromosomal contacts. Consistent identification of HIRs would be informative with respect to inferred 3D architecture since the corresponding regions of the reconstruction would have an elevated number of k nearest neighbors (kNNs). More generally, we anticipate a monotone decreasing relationship between StatDn values and kNN distances. After initially evaluating the reproducibility of StatDns across replicate Hi-C data sets, we use this implied StatDn - kNN relationship to gauge the utility of StatDns for reconstruction validation, making recourse to both real and simulated examples. CONCLUSIONS:Our analyses demonstrate that, as constructed, StatDns do not provide a suitable measure for assessing the accuracy of 3D genome reconstructions. Whether this is attributable to specific choices surrounding normalization in defining StatDns or to the logic underlying their very formulation remains to be determined.

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A compendium of chromatin contact maps reflecting regulation by chromatin remodelers in budding yeast

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