Building a 4D Nucleome State Landscape in Human IPSCS: Integrated Analysis of the Organization and Function of Nuclear Bodies

The Allen Institute for Cell Science is developing a state space of stem cell structural signatures to understand the principles by which cells reorganize as they traverse the cell cycle and differentiate. To do this, we have developed a pipeline that generates high-replicate, dynamic image data of cell organization and activities in human induced pluripotent stem cell (hiPSC) lines (the Allen Cell Collection at www.allencell.org). To study the organization of the nucleus at multiple spatial scales, 17 of these lines express an endogenous monoallelic EGFP-tagged protein that represents a key nuclear structure. Tagged structures include major nuclear landmarks (nuclear lamina, pores, speckles and nucleoli), chromatin structure (histone H2B, HP1-beta, and EZH2), key proteins in chromatin looping (CTCF, SMC1A), chromatin loci (telomeres and DNA replication sites), RNA polymerase, and two pluripotency transcription factors. We take advantage of the thousands of 3D single cell images collected for each structure and use our image analysis tools combined with deep learning-based label free technology to create integrated models of three nuclear reference structures: the lamina, nucleoli and speckles. From analysis of these models we find 1) evidence that speckles are continuously produced as a cell progresses through interphase and 2) evidence that nucleoli and speckles coordinate their total size. In collaboration with the 4D Nucleome, we will also be incorporating 3D genome structures into these models by combining image-based spatial constraints with 3D genome mapping assays. Last, to get at the functional role of these nuclear structures, we performed a flow-based CRISPRi screen for genes that perturbed nucleolar morphology. The primary hits include genes that regulate both transcription and epigenetics, preliminarily hinting at a relationship between nucleolar structure and regulation of gene expression in hiPSCs.