Enrichment Workflows for Single Cell Genome Analysis
Integration of Targeted Enrichment Methods for Single-cell Genomic Studies Using the ResolveDNA® Product Solution
BioSkryb Genomics has established multiple workflows to enable low DNA input and single-cell genomics. These workflows highlight how next generation amplification, library preparation and sequencing technologies yield high quality single-cell targeted panel data.
Heterogeneity within and between cellular populations dictates the fate of all tissues in both normal development and disease pathogenesis. The development of single-cell approaches has revealed amazing diversity across tissues. While the majority of methods to define cellular variation are based on the transcriptomics1,2, ascertaining genomic diversity enables the understanding of the underlying blueprint of cellular heterogeneity. Numerous biological studies have demonstrated that accurate identification of genetic variation in single cells is essential for understanding the role of mutation in normal development and in disease3,4,5. Key to detecting this diversity is the ability to faithfully replicate the genomes that are not detectable reliably at the single cell level without prior amplification. The development of Primary Templatedirected Amplification (Figure 1) for individual cells and low DNA inputs allows for amplification with unprecedented uniformity, providing revolutionary sequencing breadth and sensitivity6.
While whole genome sequencing (WGS) using next generation sequencing (NGS) uncovers striking single nucleotide variation (SNV) across the entire genome, much of intergenic and intronic regions remain unannotated. Due to this and the cost of WGS, more cost effective approaches, such as whole exome sequencing, (WES) are desirable. WES has broad coverage of all annotated and expressed genes and is able to interrogate the impact of genetic variation. Alternatively, user-selected specific regions of the genome for high depth NGS analysis provide a cost effective approach allowing increased cellular
throughput and broad genomic analysis of a subset of genes to the entire exome. As a result, BioSkryb Genomics has paired several downstream enrichment products (Figure 2) with our ResolveDNA8 whole genome amplification product solution for both experimental models and clinical samples9.
Each workflow provided here, is further detailed in a discrete BioSkryb Genomics Technical note which will guide the user on the process of generating enriched NGS-ready libraries for single cell genomic studies. All Techincal Notes can be found at BioSkryb.com.
Illumina DNA Prep for Enrichment
A workflow demonstrating both WGS and genome enrichment using Illumina DNA preparation for Enrichment with the TruSight One Expanded panel containing 6700 genes, with ~16.5 megabase of coverage in the genome (~0.5% of the comprehensive genome).
Twist BioSciences Human Core Exome Enrichment
A workflow which utilizes double-stranded DNA (dsDNA) probes within a comprehensive target enrichment kit for exome and targeted sequencing. Using dsDNA as opposed to single-stranded DNA captures all specified sequences uniformly. The TWIST Human Core Exome covers nearly the entire exome (~34 megabases; ~1.0 % of the comprehensive genome).
Integrated DNA Technologies V2 Exome
To provide increased depth of coverage and enable high multiplexing of samples, the xGen Exome Research Panel v2 targets only the coding sequences of human coding genes in the RefSeq 109 database. The xGen Exome Research Panel v2 consists of 415,115 individually synthesized and qualitycontrolled xGen Lockdown Probes. The panel spans a 34 Mb target region (19,433 genes) of the human genome and covers 39 Mb of probe space.
- Pollen, A.A., et al., Low-coverage single-cell mRNA sequencing reveals cellular heterogeneity and activated signaling pathways in developing cerebral cortex. Nat Biotechnol, 2014. 32(10): p. 1053-8.
- Nowakowski, T.J., et al., Spatiotemporal gene expression trajectories reveal developmental hierarchies of the human cortex. Science, 2017. 358(6368): p. 1318- 1323.
- Navin, N.E., Delineating cancer evolution with single-cell sequencing. Sci Transl Med, 2015. 7(296): p. 296fs29.
- Xu, X., et al., Single-cell exome sequencing reveals single-nucleotide mutation characteristics of a kidney tumor. Cell, 2012. 148(5): p. 886-95.
- Alexander, J., et al., Utility of Single-Cell Genomics in Diagnostic Evaluation of Prostate Cancer. Cancer Res, 2018. 78(2): p. 348-358
- de Bourcy, C.F., et al., A quantitative comparison of single-cell whole genome amplification methods. PLoS One, 2014. 9(8): p. e105585.
- Gonzalez-Pena, V., et al., Accurate genomic variant detection in single cells with primary template-directed amplification. Proc Natl Acad Sci U S A, 2021. 118(24).
- BioSkryb Genomics, i., ResolveDNA Whole Genome Amplification Kit For high-quality single-cell and low-input DNA amplification, in www.bioskryb.com, B. Genomics, Editor. 2021, BioSkryb Genomics: Durham, NC. USA
- Zawistowski, J., et al., Single-cell oncogenic mechanistic heterogeneity defined by PTA in primary Ductal Carcinoma In Situ, in Application note, Bioskryb Genomics, Editor. 2021, BioSkryb Genomics: www.bioskryb.com. p. 1-5.
For more information or technical assistance: email@example.com