Here, using population-based modeling on ensemble Hi-C data, the authors provide an expansive overview of how the genic chromatin microenvironment influences its potential involvement in different functions, such as transcription, DNA replication, and chromatin compartmentalization. Their results unveil a key role of nuclear speckles in genome organization.The nuclear folding of chromosomes relative to nuclear bodies is an integral part of gene function. Here, we demonstrate that population-based modeling-from ensemble Hi-C data-provides a detailed description of the nuclear microenvironment of genes and its role in gene function. We define the microenvironment by the subnuclear positions of genomic regions with respect to nuclear bodies, local chromatin compaction, and preferences in chromatin compartmentalization. These structural descriptors are determined in single-cell models, thereby revealing the structural variability between cells. We demonstrate that the microenvironment of a genomic region is linked to its functional potential in gene transcription, replication, and chromatin compartmentalization. Some chromatin regions feature a strong preference for a single microenvironment, due to association with specific nuclear bodies in most cells. Other chromatin shows high structural variability, which is a strong indicator of functional heterogeneity. Moreover, we identify specialized nuclear microenvironments, which distinguish chromatin in different functional states and reveal a key role of nuclear speckles in chromosome organization. We demonstrate that our method produces highly predictive three-dimensional genome structures, which accurately reproduce data from a variety of orthogonal experiments, thus considerably expanding the range of Hi-C data analysis.

A multitude of sequencing-based and microscopy technologies provide the means to unravel the relationship between the three-dimensional organization of genomes and key regulatory processes of genome function. Here, we develop a multimodal data integration approach to produce populations of single-cell genome structures that are highly predictive for nuclear locations of genes and nuclear bodies, local chromatin compaction and spatial segregation of functionally related chromatin. We demonstrate that multimodal data integration can compensate for systematic errors in some of the data and can greatly increase accuracy and coverage of genome structure models. We also show that alternative combinations of different orthogonal data sources can converge to models with similar predictive power. Moreover, our study reveals the key contributions of low-frequency ('rare') interchromosomal contacts to accurately predicting the global nuclear architecture, including the positioning of genes and chromosomes. Overall, our results highlight the benefits of multimodal data integration for genome structure analysis, available through the Integrative Genome Modeling software package.The Integrative Genome Modeling platform is a tool for population-based three-dimensional genome structure modeling and analysis by integrating various experimental data sources.

MEF2 and NKX2-5 transcription factors interact with each other in cardiogenesis and are necessary for normal heart formation. Despite evidence suggesting that these two transcription factors function synergistically and possibly through direct physical interactions, molecular mechanisms by which they interact are not clear. Here we determined the crystal structures of ternary complexes of MEF2 and NKX2-5 bound to myocardin enhancer DNA in two crystal forms. These crystal structures are the first example of human MADS-box/homeobox ternary complex structures involved in cardiogenesis. Our structures reveal two possible modes of interactions between MEF2 and NKX2-5: MEF2 and NKX bind to adjacent DNA sites to recognize DNA in cis; and MEF2 and NKX bind to different DNA strands to interact with each other in trans via a conserved protein-protein interface observed in both crystal forms. Disease-related mutations are mapped to the observed protein-protein interface. Our structural studies provide a starting point to understand and further study the molecular mechanisms of the interactions between MEF2 and NKX2.5 and their roles in cardiogenesis. (C) 2020 Published by Elsevier Ltd.

Limitations in the applicability, accuracy, and precision of individual structure characterization methods can sometimes be overcome via an integrative modeling approach that relies on information from all available sources, including all available experimental data and prior models. The open-source Integrative Modeling Platform (IMP) is one piece of software that implements all computational aspects of integrative modeling. To maximize the impact of integrative structures, the coordinates should be made publicly available, as is already the case for structures based on X-ray crystallography, NMR spectroscopy, and electron microscopy. Moreover, the associated experimental data and modeling protocols should also be archived, such that the original results can easily be reproduced. Finally, it is essential that the integrative structures are validated as part of their publication and deposition. A number of research groups have already developed software to implement integrative modeling and have generated a number of structures, prompting the formation of an Integrative/Hybrid Methods Task Force. Following the recommendations of this task force, the existing PDBx/mmCIF data representation used for atomic PDB structures has been extended to address the requirements for archiving integrative structural models. This IHM-dictionary adds a flexible model representation, including coarse graining, models in multiple states and/or related by time or other order, and multiple input experimental information sources. A prototype archiving system called PDB-Dev ( https://pdb-dev.wwpdb.org ) has also been created to archive integrative structural models, together with a Python library to facilitate handling of integrative models in PDBx/mmCIF format.

Packaging of the genome in the nucleus is a non-random process that is thought to directly contribute to cell type-specific transcriptomes, although this hypothesis remains untested. Epigenome architecture, as assayed by chromatin conformation capture techniques, such as Hi-C, has recently been described in the mammalian cardiac myocyte and found to be remodeled in the setting of heart failure. In the present study, we sought to determine whether the structural features of the epigenome are conserved between different cell types by investigating Hi-C and RNA-seq data from heart and liver. Investigation of genes with enriched expression in heart or liver revealed nuanced interaction paradigms between organs: first, the log(2) ratios of heart:liver (or liver:heart) intrachromosomal interactions are higher in organ-specific gene sets (p = 0.009), suggesting that organ-specific genes have specialized chromatin structural features. Despite similar number of total interactions between cell types, intrachromosomal interaction pro files in heart but not liver demonstrate that genes forming promoter-to-transcription-end-site loops in the cardiac nucleus tend to be involved in cardiac-related pathways. The same analysis revealed an analogous organ-specific interaction pro file for liver-specific loop genes. Investigation of A/B compartmentalization (marker of chromatin accessibility) revealed that in the heart, 66.7% of cardiac-specific genes are in compartment A, while 66.1% of liver-specific genes are found in compartment B, suggesting that there exists a cardiac chromatin topology that allows for expression of cardiac genes. Analyses of interchromosomal interactions revealed a relationship between interchromosomal interaction count and organ-specific gene localization (p = 2.2 x 10(-16)) and that, for both organs, regions of active or inactive chromatin tend to segregate in 3D space (i.e., active with active, inactive with inactive). 3D models of topologically associating domains (TADs) suggest that TADs tend to interact with regions of similar compartmentalization across chromosomes, revealing trans structural interactions contributing to genomic compartmentalization at distinct structural scales. These models reveal discordant nuclear compaction strategies, with heart packaging compartment A genes preferentially toward the center of the nucleus and liver exhibiting preferential arrangement toward the periphery. Taken together, our data suggest that intra- and interchromosomal chromatin architecture plays a role in orchestrating tissue-specific gene expression.

The myocyte enhancer factor 2 (MEF2) family of transcription factors plays important roles in developmental processes and adaptive responses. Although MEF2 proteins are known to bind DNA in the nucleus to regulate specific gene expression, there are reports that show that MEF2 also functions in the cytoplasm. Previous structural studies of MEF2 focused exclusively on DNA-bound MEF2 with and without various corepressors or coactivators. While these studies have established a comprehensive structural model of DNA recognition and cofactor recruitment by MEF2, the structure of MEF2 not bound to DNA, which include cytoplasmic MEF2 and free MEF2 in the nucleus, is unknown. Here we determined the structure of the MADS-box/MEF2 domain of MEF2B without DNA nor cofactor. The Apo structure of MEF2B reveals a largely preformed DNA binding interface that may be important for recognizing the shape of DNA from the minor groove side. In addition, our structure also reveals that the C-terminal helix of the MEF2-specific domain could flip up to bind to the hydrophobic groove that serves as the binding sites of MEF2 transcription cofactors. These observations shed new insights into DNA binding and cofactor interaction by MEF2 proteins.

MEF2B is a major target of somatic mutations in non-Hodgkin lymphoma. Most of these mutations are non synonymous substitutions of surface residues in the MADS-box/MEF2 domain. Among them, D83V is the most frequent mutation found in tumor cells. The link between this hotspot mutation and cancer is not well understood. Here we show that the D83V mutation induces a dramatic alpha-helix to beta-strand switch in the MEF2 domain. Located in an alpha-helix region rich in beta-branched residues, the D83V mutation not only removes the extensive helix stabilization interactions but also introduces an additional beta-branched residue that further shifts the conformation equilibrium from alpha-helix to beta-strand. Cross-database analyses of cancer mutations and chameleon sequences revealed a number of well-known cancer targets harboring beta-strand favoring mutations in chameleon alpha-helices, suggesting a commonality of such conformational switch in certain cancers and a new factor to consider when stratifying the rapidly expanding cancer mutation data. (C) 2018 Published by Elsevier Ltd.

Nuclear pore complexes play central roles as gatekeepers of RNA and protein transport between the cytoplasm and nucleoplasm. However, their large size and dynamic nature have impeded a full structural and functional elucidation. Here we determined the structure of the entire 552-protein nuclear pore complex of the yeast Saccharomyces cerevisiae at sub-nanometre precision by satisfying a wide range of data relating to the molecular arrangement of its constituents. The nuclear pore complex incorporates sturdy diagonal columns and connector cables attached to these columns, imbuing the structure with strength and flexibility. These cables also tie together all other elements of the nuclear pore complex, including membrane-interacting regions, outer rings and RNA-processing platforms. Inwardly directed anchors create a high density of transport factor-docking Phe-Gly repeats in the central channel, organized into distinct functional units. This integrative structure enables us to rationalize the architecture, transport mechanism and evolutionary origins of the nuclear pore complex.