Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.
Swiss Cancer Center Leman, Lausanne, Switzerland.
Nat Commun. 2021 May 10;12(1):2439. doi: 10.1038/s41467-021-22666-3.
Chromatin compartmentalization reflects biological activity. However, inference of chromatin sub-compartments and compartment domains from chromosome conformation capture (Hi-C) experiments is limited by data resolution. As a result, these have been characterized only in a few cell types and systematic comparisons across multiple tissues and conditions are missing. Here, we present Calder, an algorithmic approach that enables the identification of multi-scale sub-compartments at variable data resolution. Calder allows to infer and compare chromatin sub-compartments and compartment domains in >100 cell lines. Our results reveal sub-compartments enriched for poised chromatin states and undergoing spatial repositioning during lineage differentiation and oncogenic transformation.
染色质区室化反映了生物活性。然而,从染色体构象捕获(Hi-C)实验推断染色质亚区室和区室域受到数据分辨率的限制。因此,这些仅在少数几种细胞类型中得到了描述,并且缺少跨多种组织和条件的系统比较。在这里,我们提出了 Calder,这是一种算法方法,可实现可变数据分辨率下多尺度亚区室的识别。Calder 允许在 >100 种细胞系中推断和比较染色质亚区室和区室域。我们的结果揭示了富含处于静止状态的染色质状态的亚区室,并在谱系分化和致癌转化过程中发生空间重定位。