Academic Background

Job Dekker received his B.S. (1993) and his Ph.D. (1997) from the University of Utrecht, The Netherlands. From 1998 to 2003, he was a post-doctoral fellow at Harvard University during which time he was awarded an NWO-TALENT stipendium, an EMBO long-term fellowship and a fellowship from The Medical Foundation / Charles A. King Trust. Dr. Dekker joined the University of Massachusetts Medical School as an Assistant Professor in the Program of Gene Function and Expression in the spring of 2003. In 2008 he was promoted to Associate Professor. He is a recipient of a 2007 W. M. Keck Foundation Distinguished Young Scholar in Medical Research Award, and the 2011 ASBMB Young Investigator Award.

Spatial Organization of Genomes

We study how a genome is organized in three dimensions inside the nucleus.  The spatial organization of a genome plays important roles in regulation of genes and maintenance of genome stability.  Many diseases, including cancer, are characterized by alterations in the spatial organization of the genome.  How genomes are organized in three dimensions, and how this affects gene expression is poorly understood.  To address this issue we study the genomes of human and yeast, using a set of powerful molecular and genomic tools that we developed.

From linear sequence to three-dimensional organization

Although the DNA of chromosomes is a linear sequence, the living genome does not function in a linear fashion.  This is most clearly illustrated by the fact that genes are often regulated by elements that can be located far away along the genome sequence. Recent evidence shows that regulatory elements can act over large genomic distances by engaging in direct physical interactions with target genes, resulting in the formation of chromatin loops.  Based on these observations we have proposed that the spatial organization of the genome resembles a three-dimensional network that is driven by physical associations between genes and regulatory elements, both in cis (along the same chromosome) and in trans (between different chromosomes) (Dekker (2006), Nature Methods, 3(1): 17-21).

How does the spatial organization of a genome relate to its regulation and function?

In each cell type a distinct set of genes is expressed and therefore the spatial organization of the genome will likely be cell-type specific.  Insights into the mechanisms that modulate the spatial organization of the genome will greatly contribute to a better understanding of tissue-specific gene regulation and may reveal causes of human diseases that are due to defects in these processes.

In order to understand the spatial organization of a genome we try to answer the following questions.  Which regulatory elements interact with each of the genes in the human genome?  What drives the specificity of these interactions?  Can we identify proteins that mediate these interactions?  How do interactions between regulatory elements and genes result in activation and repression of genes?  How do defects in these interactions result in human disease?  Can we use information about chromatin interactions to generate three-dimensional models of chromosomes?

Tools we developed for mapping the spatial organization of genomes: 3C, 5C and Hi-C

We developed Chromosome Conformation Capture (3C), which is used to detect physical interactions between genomic elements (Dekker et al. Science, 2002).  Using 3C we, and others, discovered that gene regulation is mediated by the three-dimensional organization of chromosomes that brings genes and their regulatory elements in close spatial proximity.  3C is now widely used and already has had a major impact on studies of genome regulation.

Large-scale detection of long-range chromatin interactions will be instrumental in mapping genome-wide networks of communication between genomic elements and the determination of the three-dimensional folding of the genome.  My group was the first to combine 3C with ultra-high-throughput DNA sequencing, thereby dramatically increasing the scale at which interactions between genomic loci can be studied.  Specifically, we have developed 5C, a high-throughput version of 3C for large-scale mapping of chromatin interaction networks (Dostie et al. Genome Res. 2006).  To enable the community to adopt 5C and related technologies we have developed "my5C", a publicly available set of computational tools for design of 5C studies and for visualization and analysis of any large chromatin interaction data sets (my5C.umassmed.edu; Lajoie et al. Nature Methods 2009).

Ultimately we aim to obtain detailed insights into the three-dimensional arrangements of complete genomes at Kb resolution.  To this end we recently developed the Hi-C technology: a genome-wide and unbiased method that combines 3C with deep sequencing (Lieberman-Aiden, van Berkum et al. Science 2009).  We have applied Hi-C to generate the first comprehensive and unbiased long-range interaction maps of the human genome.  Hi-C data reveal both known hallmarks of nuclear organization (e.g. formation of chromosome territories, and preferred co-location of particular pairs of chromosomes) as well as novel folding principles of chromosomes.  First, we found that the human genome is divided over two types of spatial compartments, one containing active chromatin, and one containing all inactive segments of the genome.  Second, we discovered a novel higher order chromatin folding motif: at the megabase scale, our data are consistent with a model in which chromatin is described by a polymer state known as the fractal globule: a knot-free conformation that enables maximally dense packing while preserving the ability to easily fold and unfold any genomic locus.   This conformation is an extremely efficient solution for packing long chromosomes inside the nucleus.  Hi-C data for GM06990 lymphoblastoid cells and for K562 erythroleukemia cells is available in a user friendly format at our website: http://hic.umassmed.edu.

Chromatin looping in the human beta-globin locus

The human beta-globin locus consists of five beta-globin-like genes (e, Ag, Gg, d and b) and one beta-globin pseudogene (y).  These genes are developmentally regulated by a single element, the Locus Control Region (LCR) located upstream of the gene cluster.  This locus has served as a powerful model system to study long-range gene regulation.  The LCR was found to directly interact with the expressed beta-globin-like genes resulting in the formation of large chromatin loops.  For instance in K562 cells, that express high levels of g-globin, we found that the LCR strongly interacts with the g-globin genes but not with the other beta-globin-like genes (Dostie et al. (2006), Genome Research, 16(10): 1299-1309).  Interestingly, the LCR also interacts with a genomic element located downstream of the globin genes, although the role of this interaction is currently unclear.  A schematic representation of these looping interactions is presented in Figure 2. 

We continue to study the human beta-globin locus to understand the molecular and biochemical mechanisms that drive developmental dynamics of long-range gene regulation.

Three-dimensional organization of chromosomes and chromatin domains

As a first step towards studying the spatial organization of entire chromosomes we have used 3C to determine the three-dimensional structure of yeast chromosome III (Dekker et al. (2002), Science, 295: 1306-1311).  We generated a matrix of interaction frequencies and developed mathematical tools to determine a population-average three-dimensional model of this ~320 kb chromosome based on the pattern of chromatin interactions (Figure 3).  Chromosome III emerged as a contorted ring, due to prominent interactions between the sub-telomeric regions. 

We have also analyzed the effect of gene activation on the general organization of a 150 kb chromatin domain around the FMR1 gene on the human X-chromosome.  We found that gene activation results in chromatin decondensation throughout a surprisingly large 50 kb region surrounding the active promoter (Gheldof et al. (2006), PNAS 103(33): 12463-12468). The molecular mechanisms that drive these large-scale conformational changes are currently being studied.

We continue to employ 3C and 5C to study the overall spatial organization of chromosomes and chromosome domains in yeast and human cells.

For more information on the work in my laboratory, please see our lab website at http://my5c.umassmed.edu/welcome/welcome.php

Figures

Figure 1.   (a) Genes (blue rectangles) and regulatory elements (red circles) are linearly organized along chromosomes (top), but as a result of specific interactions between elements (indicated by arrows, both in cis and in trans) a complex three-dimensional network is formed inside the cell (bottom).  (b) Schematic representation of the 3C assay.  Chromatin is cross-linked, digested with a restriction enzyme and then ligated.  Specific ligation products can be detected by PCR.  [Figure from Dekker (2006), Nature Methods, 3(1): 17-21].

Figure 2.   Schematic representation of the human beta-globin locus.  Activation of the g-globin genes in K562 cells involves interactions between the LCR and the activated genes resulting in a large (~40 kb) chromatin loop.  The LCR also interacts with an element located downstream of the locus (3’HS1).

Figure 3. Spatial organization of yeast chromosome III (~ 320 kb) as determined by Chromosome Conformation Capture (3C). 3C was applied to determine the frequency with which several loci along the chromosome interact.  Interaction frequencies were then used to model the average spatial organization of the chromosome.  Interactions between the telomeres result in the formation of a ring-like structure with a diameter of around 300 nm.

Laboratory Personnel

Sharon Briggs, Financial Assistant, Grant & Contract Specialist
Jon-Matthew Belton, Graduate Student
Johan Gibcus, Postdoctoral Fellow
Gaurav Jain, Bioinformatician Level I
Bryan Lajoie, Bioinformatician Level II
Rachel McCord, Postdoctoral Fellow
Natalia Naumova, Postdoctoral Fellow
Amartya Sanyal, Postdoctoral Fellow
Emily Smith, Graduate Student
Ye Zhan, Research Associate