Three-dimensional genome organization is an important higher order transcription regulation mechanism that can be studied with the chromosome conformation capture techniques. Here, we combined chromatin organization analysis by chromosome conformation capture-carbon copy, computational modeling and epigenomics to achieve the first integrated view, through time, of a connection between chromatin state and its architecture. We used this approach to examine the chromatin dynamics of the HoxA cluster in a human myeloid leukemia cell line at various stages of differentiation. We found that cellular differentiation involves a transient activation of the 5′-end HoxA genes coinciding with a loss of contacts throughout the cluster, and by specific silencing at the 3′-end with H3K27 methylation. The 3D modeling of the data revealed an extensive reorganization of the cluster between the two previously reported topologically associated domains in differentiated cells. Our results support a model whereby silencing by polycomb group proteins and reconfiguration of CTCF interactions at a topologically associated domain boundary participate in changing the HoxA cluster topology, which compartmentalizes the genes following differentiation.

Human health is related to information stored in our genetic code, which is highly variable even amongst healthy individuals. Gene expression is orchestrated by numerous control elements that may be located anywhere in the genome, and can regulate distal genes by physically interacting with them. These DNA contacts can be mapped with the chromosome conformation capture and related technologies. Several studies now demonstrate that gene expression patterns are associated with specific chromatin structures, and may therefore correlate with chromatin conformation signatures. Here, we present an overview of genome organization and its relationship with gene expression. We also summarize how chromatin conformation signatures can be identified and discuss why they might represent ideal biomarkers of human disease in such genetically diverse populations.

The human genome must be tightly packaged in order to fit inside the nucleus of a cell. Genome organization is functional rather than random, which allows for the proper execution of gene expression programs and other biological processes. Recently, three-dimensional chromatin organization has emerged as an important transcriptional control mechanism. For example, enhancers were shown to regulate target genes by physically interacting with them regardless of their linear distance and even if located on different chromosomes. These chromatin contacts can be measured with the “chromosome conformation capture” (3C) technology and other 3C-related techniques. Given the recent innovation of 3C-derived approaches, it is not surprising that we still know very little about the structure of our genome at high-resolution. Even less well understood is whether there exist distinct types of chromatin contacts and importantly, what regulates them. A new form of regulation involving the expression of long non-coding RNAs (lncRNAs) was recently identified. lncRNAs are a very abundant class of non-coding RNAs that are often expressed in a tissue-specific manner. Although their different subcellular localizations point to their involvement in numerous cellular processes, it is clear that lncRNAs play an important role in regulating gene expression. How they control transcription however is mostly unknown. In this review, we provide an overview of known lncRNA transcription regulation activities. We also discuss potential mechanisms by which ncRNAs might exert three-dimensional transcriptional control and what recent studies have revealed about their role in shaping our genome.

BackgroundAlthough genetic or epigenetic alterations have been shown to affect the three-dimensional organization of genomes, the utility of chromatin conformation in the classification of human disease has never been addressed.ResultsHere, we explore whether chromatin conformation can be used to classify human leukemia. We map the conformation of the HOXA gene cluster in a panel of cell lines with 5C chromosome conformation capture technology, and use the data to train and test a support vector machine classifier named 3D-SP. We show that 3D-SP is able to accurately distinguish leukemias expressing MLL-fusion proteins from those expressing only wild-type MLL, and that it can also classify leukemia subtypes according to MLL fusion partner, based solely on 5C data.ConclusionsOur study provides the first proof-of-principle demonstration that chromatin conformation contains the information value necessary for classification of leukemia subtypes.

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