The field of 3D genomics, which has already boosted our understanding of gene regulation, is now shedding light on the importance of genomic organization and function. The 3D organization of genomes has functional implications for individual genes and their interactions with other elements. For example, a gene in close physical proximity to an enhancer might be upregulated, whereas a gene that is tightly compacted into heterochromatin might be downregulated. Furthermore, even though all cells of an organism share a common genome sequence, the manner in which a genome is packed into a nucleus can vary among cells, which influences cell-type-specific gene expression.
A range of methods have developed to study how a genome is organized in three dimensions within the nucleus. The widespread method known as chromosome conformational capture technology (3C) reveals how chromosomes are folded in 3-dimensional space by looking at the relationship in space between two loci in a genome, and has prompted the development of related methods. For example, circular chromosome conformation capture (4C) looks at the relationship between one locus with respect to the rest of the genome. High-throughput chromosome conformation capture (HiC) combines next-generation sequencing with 3C to investigate the entire genome in 3D space. This article looks at some innovative 3D genomics technologies that are opening windows into genomic organization and function.
3D genomics sample prep
Every genomics experiment starts with sample preparation, where it’s important to remember the adage “garbage in, garbage out.” Maximizing the quality of your starting material is critical for success. Covaris offers support for the ever-important sample-preparation steps that are key for 3D genomics methods such as HiC and ChIA-PET (see below). Their clients work in a range of 3D genomics topics, such as identifying disease risk variants based on 3D genomic organization, distinguishing functional compartments such as promoter or non-promoter loops or other substructures, and understanding regulatory components underlying higher order chromatin structure.
The Covaris Focused-ultrasonicators use their Adaptive Focused Acoustics® (AFA®) technology, which shears genomic sample material using bursts of focused high-frequency acoustic energy. Because of the highly focused energy supply, the disadvantages of conventional sonicators are avoided (i.e. heat damage, inconsistency, overprocessing).
The resulting sheared genomic fragments fall into a narrower size distribution, which obviates the need for additional size selection steps, according to Angela Garding, field application scientist at Covaris. “The isothermal processing further enables unique epitope preservation, which is essential when mapping proteins involved in higher order chromatin structure,” she says. “For assays starting from scarce input samples such as in situ HiC, scientists value mechanical nuclei isolation using AFA for efficient nuclei extraction from versatile input samples.” Covaris also offers truChIP® Chromatin Shearing Kits and other sample-preparation tools designed to optimize chromatin extraction and shearing using AFA.
3D genomics in single cells
A series of methods of studying chromatin interactions was developed over the past 10 years by Chia-Lin Wei, director of genome technologies at The Jackson Laboratory, and colleagues, which they termed chromatin interaction analysis by paired-end tag sequencing (ChIA-PET). These technologies for 3D genomics have been further improved at single-cell resolution in recent years to examine protein-mediated 3D chromatin interactions. “We are specifically looking for transactivating factors, including protein transcription factors in cancer complexes, or RNA polymerase core machinery or repressive complexes,” says Wei.
The Wei lab explores the general principles governing protein-mediated chromatin interactions and chromatin topological folding. She is interested in how chromatin configurations during the pathological state play a role in inducing diseases such as cancer. “In my lab, we study this during tumorigenesis, for example, or during drug response or tumor evolution, by looking at the changes in the chromatin configuration and in the transcription programs,” explains Wei.
The ChIA-PET method provides high-resolution information, such as specific protein-mediated chromatin contacts at base resolution, while also generating a broader topological domain. “Currently, we’re trying to improve our methodology named ChIA-Drop for use with single cells and individual chromatin complexes, which will be ideal for limited or scarce sample types,” says Wei. “We can also use this methodology to study heterogeneity among cell populations, for example in brain or blood.”
3D genomics applied to regulating gene expression
The lab of Ana Pombo, professor at the Humboldt University of Berlin and researcher at the Max Delbrueck Centre for Molecular Medicine, studies how 3D genome structure is established and the role it plays in regulating gene expression. “We are especially interested in discovering how 3D genome structure may contribute to homeostasis of gene expression, how it supports reliable gene activation and deactivation, how genes retain their expression status in a context of changes in neighboring genes, and how the structure itself controls gene expression and efficient RNA maturation,” says Pombo.
They developed a method called genome architecture mapping (GAM), which measures 3D proximities between genomic loci and infers chromatin compaction without using ligation, through sequencing DNA extracted from thin sections sliced from many different nuclei. They also use cryo-FISH, a form of fluorescence in situ hybridization (FISH) performed on thin cryosections of fixed tissue.
The advantages of these methods is that they preserve nuclear structure and minimize the loss of proteins and RNA responsible for the nuclear structure. “Both GAM and cryo-FISH are performed on very well-preserved cells or tissues, and both retain single-cell information that can help relate variability in 3D genome structure with on/off states of gene expression that go beyond correlation,” says Pombo.
Pombo believes that future advances will include integrating multi-omics information to understand the interactions between cell state, genome conformation, and gene expression. “[These] have the power to help understand dynamics, and importantly can be applied in real patient samples,” she says.