ScGET-seq
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Single-cell genome and epigenome by transposases sequencing (scGET-seq) is a DNA sequencing method for profiling open and closed chromatin. In contrast to single-cell assay for transposase-accessible chromatin with sequencing (scATAC-seq), which only targets active euchromatin[1], scGET-seq is also capable of probing inactive heterochromatin[2].
This is achieved through the use of TnH, which is created by linking the chromodomain (CD) of heterochromatin protein-1-alpha (HP-1) to the Tn5 transposase. TnH is then able to target histone 3 lysine 9 trimethylation (H3K9me3), a marker for heterochromatin[3].
Akin to RNA velocity, which uses the ratio of spliced to unspliced RNA to infer the kinetics of changes in gene expression over the course of cellular development[4], the ratio of TnH to Tn5 signals obtained from scGET-seq can be used to calculate chromatin velocity, which measures the dynamics of chromatin accessibility over the course of cellular developmental pathways[2].
History
Transcriptional regulation is tightly linked to chromatin states. Chromatin that is open, or permissive to transcription, make up only 2-3% of the genome, but encompass 94.4% of transcription factor binding sites[5][6]. Conversely, more tightly packed DNA, or heterochromatin, is responsible for genome organization and stability[7]. Chromatin density also changes over the course of cellular differentiation processes[8], but there is a lack of high-throughput sequencing methods for directly assaying heterochromatin.
Many genomic-related diseases such as cancer are highly linked to changes in their epigenome. Cancers in particular are characterized by single-cell heterogeneity, which can drive metastasis and treatment resistance[9][10]. The mechanisms that underlie these processes are still largely unknown, although the advent of single-cell technologies, including single-cell epigenomics, has contributed greatly to their elucidation[11].
In 2015, ATAC-seq, which uses the Tn5 transposase to fragment and tag accessible chromatin, or euchromatin, for sequencing, became feasible at the single-cell resolution[12]. scGET-seq builds upon this technology by also providing information on heterochromatin, providing a more comprehensive look at chromatin structure and dynamics within each cell[13].
Technology and Methods
![](http://upload.wikimedia.org/wikipedia/commons/thumb/8/8a/ScGET-seq_Methods_Overview.png/220px-ScGET-seq_Methods_Overview.png)
Sample Preparation
Sample preparation for scGET-seq starts with obtaining a suspension of nuclei from cells using a method appropriate for the starting material[14].
The next step is to produce the TnH transposase. Tn5 is a transposase that cuts and ligates adapters to genomic regions unbound by nucleosomes (open chromatin)[15]. HP-1a is a member of the HP1 family and is able to recognize and specifically bind to H3K9me3[16][17]. Its chromodomain uses an induced-fit mechanism for recognizing this chromatin modification[18]. Linking the first 112 amino acids of HP-1a containing the chromodomain to Tn5 using a three poly-tyrosine-glycine-serine (TGS) linker leads to the creation of the TnH transposase, which is capable of targeting heterochromatin marked by H3K9me3[2].
Library preparation is done using a modified protocol for single-cell ATAC-seq[19], where the nuclei suspension is sequentially incubated with the Tn5 transposase first, and then TnH[2].
Data Analysis
Data Pre-processing
- Post-sequencing, reads need to be demultiplexed and mapped to the appropriate reference genome. Duplicated reads are identified and removed.
- "Peaks", or regions in the DNA enriched in the number of reads mapped, are identified.
- Quality control is performed, and cells with low numbers of reads or few detected features are filtered out.
![](http://upload.wikimedia.org/wikipedia/commons/thumb/3/36/Differences_between_scGET-seq_and_scATAC-seq.png/220px-Differences_between_scGET-seq_and_scATAC-seq.png)
Applications
Current
By using the ratio of Tn5 to TnH signals, quantitative values describing how quickly and in what direction chromatin remodelling is taking place can be calculated (chromatin velocity)[2]. By isolating regions that are most dynamic and identifying which transcription factors bind there, chromatin velocity can be used to infer the dynamic epigenetic processes happening within a given cell and the contributions of various transcription factors to those processes[2].
Future
Chromatin remodelling precedes changes in gene expression and enhances the understanding of trajectories and mechanisms of cellular changes[20][21]. Thus, platforms and tools for integration of multimodal data are areas of active research[22][23][24]. Incorporating temporal and directionality elements through integration of chromatin velocity with RNA velocity has been proposed to reveal even more information about differentiation pathways[25][26].
Limitations
scGET-seq has some of the same limitations as scATAC-seq. Both processes require nuclei samples from viable cells, and high cellular viability[27]. Low cellular viability leads to high background DNA contamination that do not accurately represent authentic biological signals. Additionally, the sparsity and noisy nature of scATAC-seq and scGET-seq data makes analysis challenging, and there is no consensus yet on how to best manage this data[28].
Another limitation is that scGET-seq still needs the validation of SNVs results by bulk genome sequencing. Even though there is a high correlation of mutations between bulk exome sequencing and scGET-seq results, scGET-seq fails to capture all exome SNVs[2].
References
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